A B C D E F G H I J K L M N O P Q R S T U V W Z misc
spatstat.core-package | The spatstat.core Package |
adaptive.density | Adaptive Estimate of Intensity of Point Pattern |
addvar | Added Variable Plot for Point Process Model |
AIC.dppm | Log Likelihood and AIC for Fitted Determinantal Point Process Model |
AIC.kppm | Log Likelihood and AIC for Fitted Cox or Cluster Point Process Model |
AIC.mppm | Log Likelihood and AIC for Multiple Point Process Model |
AIC.ppm | Log Likelihood and AIC for Point Process Model |
allstats | Calculate four standard summary functions of a point pattern. |
alltypes | Calculate Summary Statistic for All Types in a Multitype Point Pattern |
anova.mppm | ANOVA for Fitted Point Process Models for Replicated Patterns |
anova.ppm | ANOVA for Fitted Point Process Models |
anova.slrm | Analysis of Deviance for Spatial Logistic Regression Models |
apply.ssf | Evaluate Expression in a Spatially Sampled Function |
AreaInter | The Area Interaction Point Process Model |
as.data.frame.envelope | Coerce Envelope to Data Frame |
as.function.fv | Convert Function Value Table to Function |
as.function.leverage.ppm | Convert Leverage Object to Function of Coordinates |
as.function.rhohat | Convert Function Table to Function |
as.function.ssf | Methods for Spatially Sampled Functions |
as.fv | Convert Data To Class fv |
as.fv.bw.optim | Convert Data To Class fv |
as.fv.data.frame | Convert Data To Class fv |
as.fv.dppm | Convert Data To Class fv |
as.fv.fasp | Convert Data To Class fv |
as.fv.fv | Convert Data To Class fv |
as.fv.kppm | Convert Data To Class fv |
as.fv.matrix | Convert Data To Class fv |
as.fv.minconfit | Convert Data To Class fv |
as.im.leverage.ppm | Methods for Leverage Objects |
as.im.scan.test | Plot Result of Scan Test |
as.im.ssf | Methods for Spatially Sampled Functions |
as.interact | Extract Interaction Structure |
as.interact.fii | Extract Interaction Structure |
as.interact.interact | Extract Interaction Structure |
as.interact.ppm | Extract Interaction Structure |
as.interact.zgibbsmodel | Methods for Gibbs Models |
as.isf.zgibbsmodel | Methods for Gibbs Models |
as.layered.msr | Convert Measure To Layered Object |
as.owin.dppm | Convert Data To Class owin |
as.owin.influence.ppm | Methods for Influence Objects |
as.owin.kppm | Convert Data To Class owin |
as.owin.leverage.ppm | Methods for Leverage Objects |
as.owin.msr | Convert Data To Class owin |
as.owin.ppm | Convert Data To Class owin |
as.owin.quadrattest | Convert Data To Class owin |
as.owin.slrm | Convert Data To Class owin |
as.ppm | Extract Fitted Point Process Model |
as.ppm.dppm | Extract Fitted Point Process Model |
as.ppm.kppm | Extract Fitted Point Process Model |
as.ppm.ppm | Extract Fitted Point Process Model |
as.ppm.profilepl | Extract Fitted Point Process Model |
as.ppp.influence.ppm | Methods for Influence Objects |
as.ppp.ssf | Methods for Spatially Sampled Functions |
auc | Area Under ROC Curve |
auc.kppm | Area Under ROC Curve |
auc.ppm | Area Under ROC Curve |
auc.ppp | Area Under ROC Curve |
auc.slrm | Area Under ROC Curve |
BadGey | Hybrid Geyer Point Process Model |
bc | Bias Correction for Fitted Model |
bc.ppm | Bias Correction for Fitted Model |
berman.test | Berman's Tests for Point Process Model |
berman.test.ppm | Berman's Tests for Point Process Model |
berman.test.ppp | Berman's Tests for Point Process Model |
bind.fv | Combine Function Value Tables |
bits.envelope | Global Envelopes for Balanced Independent Two-Stage Test |
bits.test | Balanced Independent Two-Stage Monte Carlo Test |
blur | Apply Gaussian Blur to a Pixel Image |
bw.abram | Abramson's Adaptive Bandwidths |
bw.CvL | Cronie and van Lieshout's Criterion for Bandwidth Selection for Kernel Density |
bw.CvLHeat | Bandwidth Selection for Diffusion Smoother by Cronie-van Lieshout Rule |
bw.diggle | Cross Validated Bandwidth Selection for Kernel Density |
bw.frac | Bandwidth Selection Based on Window Geometry |
bw.pcf | Cross Validated Bandwidth Selection for Pair Correlation Function |
bw.ppl | Likelihood Cross Validation Bandwidth Selection for Kernel Density |
bw.pplHeat | Bandwidth Selection for Diffusion Smoother by Likelihood Cross-Validation |
bw.relrisk | Cross Validated Bandwidth Selection for Relative Risk Estimation |
bw.scott | Scott's Rule for Bandwidth Selection for Kernel Density |
bw.scott.iso | Scott's Rule for Bandwidth Selection for Kernel Density |
bw.smoothppp | Cross Validated Bandwidth Selection for Spatial Smoothing |
bw.stoyan | Stoyan's Rule of Thumb for Bandwidth Selection |
cauchy.estK | Fit the Neyman-Scott cluster process with Cauchy kernel |
cauchy.estpcf | Fit the Neyman-Scott cluster process with Cauchy kernel |
cbind.fv | Combine Function Value Tables |
CDF | Cumulative Distribution Function From Kernel Density Estimate |
CDF.density | Cumulative Distribution Function From Kernel Density Estimate |
cdf.test | Spatial Distribution Test for Point Pattern or Point Process Model |
cdf.test.mppm | Spatial Distribution Test for Multiple Point Process Model |
cdf.test.ppm | Spatial Distribution Test for Point Pattern or Point Process Model |
cdf.test.ppp | Spatial Distribution Test for Point Pattern or Point Process Model |
cdf.test.slrm | Spatial Distribution Test for Point Pattern or Point Process Model |
circdensity | Density Estimation for Circular Data |
clarkevans | Clark and Evans Aggregation Index |
clarkevans.test | Clark and Evans Test |
closepaircounts | Count Close Pairs of Points |
clusterfield.kppm | Field of clusters |
clusterfit | Fit Cluster or Cox Point Process Model via Minimum Contrast |
clusterkernel.kppm | Extract Cluster Offspring Kernel |
clusterradius.kppm | Compute or Extract Effective Range of Cluster Kernel |
clusterradius.zclustermodel | Methods for Cluster Models |
clusterset | Allard-Fraley Estimator of Cluster Feature |
coef.dppm | Methods for Determinantal Point Process Models |
coef.fii | Methods for Fitted Interactions |
coef.kppm | Methods for Cluster Point Process Models |
coef.mppm | Coefficients of Point Process Model Fitted to Multiple Point Patterns |
coef.ppm | Coefficients of Fitted Point Process Model |
coef.slrm | Coefficients of Fitted Spatial Logistic Regression Model |
coef.summary.fii | Methods for Fitted Interactions |
coef<-.fii | Methods for Fitted Interactions |
collapse.anylist | Collapse Several Function Tables into One |
collapse.fv | Collapse Several Function Tables into One |
compareFit | Residual Diagnostics for Multiple Fitted Models |
compatible.fasp | Test Whether Function Arrays Are Compatible |
compatible.fv | Test Whether Function Objects Are Compatible |
compileK | Generic Calculation of K Function and Pair Correlation Function |
compilepcf | Generic Calculation of K Function and Pair Correlation Function |
Concom | The Connected Component Process Model |
contour.leverage.ppm | Plot Leverage Function |
contour.objsurf | Methods for Objective Function Surfaces |
contour.ssf | Plot a Spatially Sampled Function |
cor.im | Covariance and Correlation between Images |
cov.im | Covariance and Correlation between Images |
crosspaircounts | Count Close Pairs of Points |
data.ppm | Extract Original Data from a Fitted Point Process Model |
dclf.progress | Progress Plot of Test of Spatial Pattern |
dclf.sigtrace | Significance Trace of Cressie-Loosmore-Ford or Maximum Absolute Deviation Test |
dclf.test | Diggle-Cressie-Loosmore-Ford and Maximum Absolute Deviation Tests |
density.ppp | Kernel Smoothed Intensity of Point Pattern |
density.ppplist | Kernel Smoothed Intensity of Split Point Pattern |
density.psp | Kernel Smoothing of Line Segment Pattern |
density.splitppp | Kernel Smoothed Intensity of Split Point Pattern |
densityAdaptiveKernel | Adaptive Kernel Estimate of Intensity of Point Pattern |
densityAdaptiveKernel.ppp | Adaptive Kernel Estimate of Intensity of Point Pattern |
densityfun | Kernel Estimate of Intensity as a Spatial Function |
densityfun.ppp | Kernel Estimate of Intensity as a Spatial Function |
densityHeat | Diffusion Estimate of Point Pattern Intensity |
densityHeat.ppp | Diffusion Estimate of Point Pattern Intensity |
densityVoronoi | Intensity Estimate of Point Pattern Using Voronoi-Dirichlet Tessellation |
densityVoronoi.ppp | Intensity Estimate of Point Pattern Using Voronoi-Dirichlet Tessellation |
deriv.fv | Calculate Derivative of Function Values |
detpointprocfamilyfun | Construct a New Determinantal Point Process Model Family Function |
deviance.ppm | Log Likelihood and AIC for Point Process Model |
deviance.slrm | Methods for Spatial Logistic Regression Models |
dfbetas.ppm | Parameter Influence Measure |
dfbetas.slrm | Leverage and Influence Diagnostics for Spatial Logistic Regression |
dffit | Case Deletion Effect Measure of Fitted Model |
dffit.ppm | Case Deletion Effect Measure of Fitted Model |
dffit.slrm | Leverage and Influence Diagnostics for Spatial Logistic Regression |
dg.envelope | Global Envelopes for Dao-Genton Test |
dg.progress | Progress Plot of Dao-Genton Test of Spatial Pattern |
dg.sigtrace | Significance Trace of Dao-Genton Test |
dg.test | Dao-Genton Adjusted Goodness-Of-Fit Test |
diagnose.ppm | Diagnostic Plots for Fitted Point Process Model |
DiggleGatesStibbard | Diggle-Gates-Stibbard Point Process Model |
DiggleGratton | Diggle-Gratton model |
dim.detpointprocfamily | Dimension of Determinantal Point Process Model |
dimhat | Estimate Dimension of Central Subspace |
distcdf | Distribution Function of Interpoint Distance |
dkernel | Kernel distributions and random generation |
domain.dppm | Extract the Domain of any Spatial Object |
domain.influence.ppm | Methods for Influence Objects |
domain.kppm | Extract the Domain of any Spatial Object |
domain.leverage.ppm | Methods for Leverage Objects |
domain.msr | Extract the Domain of any Spatial Object |
domain.ppm | Extract the Domain of any Spatial Object |
domain.quadrattest | Extract the Domain of any Spatial Object |
domain.slrm | Extract the Domain of any Spatial Object |
dppapproxkernel | Approximate Determinantal Point Process Kernel |
dppapproxpcf | Approximate Pair Correlation Function of Determinantal Point Process Model |
dppBessel | Bessel Type Determinantal Point Process Model |
dppCauchy | Generalized Cauchy Determinantal Point Process Model |
dppeigen | Internal function calculating eig and index |
dppGauss | Gaussian Determinantal Point Process Model |
dppkernel | Extract Kernel from Determinantal Point Process Model Object |
dppm | Fit Determinantal Point Process Model |
dppMatern | Whittle-Matern Determinantal Point Process Model |
dppparbounds | Parameter Bound for a Determinantal Point Process Model |
dppPowerExp | Power Exponential Spectral Determinantal Point Process Model |
dppspecden | Extract Spectral Density from Determinantal Point Process Model Object |
dppspecdenrange | Range of Spectral Density of a Determinantal Point Process Model |
dummify | Convert Data to Numeric Values by Constructing Dummy Variables |
dummy.ppm | Extract Dummy Points Used to Fit a Point Process Model |
edge.Ripley | Ripley's Isotropic Edge Correction |
edge.Trans | Translation Edge Correction |
eem | Exponential Energy Marks |
eem.ppm | Exponential Energy Marks |
eem.slrm | Exponential Energy Marks |
effectfun | Compute Fitted Effect of a Spatial Covariate in a Point Process Model |
Emark | Diagnostics for random marking |
emend | Force Model to be Valid |
emend.ppm | Force Point Process Model to be Valid |
emend.slrm | Force Spatial Logistic Regression Model to be Valid |
envelope | Simulation Envelopes of Summary Function |
envelope.envelope | Recompute Envelopes |
envelope.kppm | Simulation Envelopes of Summary Function |
envelope.pp3 | Simulation Envelopes of Summary Function for 3D Point Pattern |
envelope.ppm | Simulation Envelopes of Summary Function |
envelope.ppp | Simulation Envelopes of Summary Function |
envelope.slrm | Simulation Envelopes of Summary Function |
envelopeArray | Array of Simulation Envelopes of Summary Function |
eval.fasp | Evaluate Expression Involving Function Arrays |
eval.fv | Evaluate Expression Involving Functions |
exactMPLEstrauss | Exact Maximum Pseudolikelihood Estimate for Stationary Strauss Process |
extractAIC.dppm | Log Likelihood and AIC for Fitted Determinantal Point Process Model |
extractAIC.kppm | Log Likelihood and AIC for Fitted Cox or Cluster Point Process Model |
extractAIC.mppm | Log Likelihood and AIC for Multiple Point Process Model |
extractAIC.ppm | Log Likelihood and AIC for Point Process Model |
F3est | Empty Space Function of a Three-Dimensional Point Pattern |
fasp.object | Function Arrays for Spatial Patterns |
Fest | Estimate the Empty Space Function or its Hazard Rate |
Fhazard | Estimate the Empty Space Function or its Hazard Rate |
Fiksel | The Fiksel Interaction |
Finhom | Inhomogeneous Empty Space Function |
fitin | Extract the Interaction from a Fitted Point Process Model |
fitin.ppm | Extract the Interaction from a Fitted Point Process Model |
fitin.profilepl | Extract the Interaction from a Fitted Point Process Model |
fitted.dppm | Prediction from a Fitted Determinantal Point Process Model |
fitted.kppm | Prediction from a Fitted Cluster Point Process Model |
fitted.mppm | Fitted Conditional Intensity for Multiple Point Process Model |
fitted.ppm | Fitted Conditional Intensity for Point Process Model |
fitted.rppm | Make Predictions From a Recursively Partitioned Point Process Model |
fitted.slrm | Fitted Probabilities for Spatial Logistic Regression |
fixef.mppm | Extract Fixed Effects from Point Process Model |
FmultiInhom | Inhomogeneous Marked F-Function |
formula.dppm | Methods for Determinantal Point Process Models |
formula.fv | Extract or Change the Plot Formula for a Function Value Table |
formula.kppm | Methods for Cluster Point Process Models |
formula.ppm | Model Formulae for Gibbs Point Process Models |
formula.slrm | Methods for Spatial Logistic Regression Models |
formula<- | Extract or Change the Plot Formula for a Function Value Table |
formula<-.fv | Extract or Change the Plot Formula for a Function Value Table |
fryplot | Fry Plot of Point Pattern |
frypoints | Fry Plot of Point Pattern |
fv | Create a Function Value Table |
fv.object | Function Value Table |
fvnames | Abbreviations for Groups of Columns in Function Value Table |
fvnames<- | Abbreviations for Groups of Columns in Function Value Table |
G3est | Nearest Neighbour Distance Distribution Function of a Three-Dimensional Point Pattern |
Gcom | Model Compensator of Nearest Neighbour Function |
Gcross | Multitype Nearest Neighbour Distance Function (i-to-j) |
Gdot | Multitype Nearest Neighbour Distance Function (i-to-any) |
Gest | Nearest Neighbour Distance Function G |
getCall.mppm | Log Likelihood and AIC for Multiple Point Process Model |
Geyer | Geyer's Saturation Point Process Model |
Gfox | Foxall's Distance Functions |
Ginhom | Inhomogeneous Nearest Neighbour Function |
Gmulti | Marked Nearest Neighbour Distance Function |
GmultiInhom | Inhomogeneous Marked G-Function |
Gres | Residual G Function |
Hardcore | The Hard Core Point Process Model |
hardcoredist | Extract the Hard Core Distance of a Point Process Model |
hardcoredist.fii | Extract the Hard Core Distance of a Point Process Model |
hardcoredist.ppm | Extract the Hard Core Distance of a Point Process Model |
harmonic | Basis for Harmonic Functions |
harmonise.fv | Make Function Tables Compatible |
harmonise.msr | Make Measures Compatible |
harmonize.fv | Make Function Tables Compatible |
has.offset | Identify Covariates Involved in each Model Term |
has.offset.term | Identify Covariates Involved in each Model Term |
Hest | Spherical Contact Distribution Function |
HierHard | The Hierarchical Hard Core Point Process Model |
hierpair.family | Hierarchical Pairwise Interaction Process Family |
HierStrauss | The Hierarchical Strauss Point Process Model |
HierStraussHard | The Hierarchical Strauss Hard Core Point Process Model |
hopskel | Hopkins-Skellam Test |
hopskel.test | Hopkins-Skellam Test |
hotbox | Heat Kernel for a Two-Dimensional Rectangle |
Hybrid | Hybrid Interaction Point Process Model |
hybrid.family | Hybrid Interaction Family |
ic | Model selection criteria for the intensity function of a point process |
ic.kppm | Model selection criteria for the intensity function of a point process |
ic.ppm | Model selection criteria for the intensity function of a point process |
idw | Inverse-distance weighted smoothing of observations at irregular points |
Iest | Estimate the I-function |
image.objsurf | Methods for Objective Function Surfaces |
image.ssf | Plot a Spatially Sampled Function |
improve.kppm | Improve Intensity Estimate of Fitted Cluster Point Process Model |
increment.fv | Increments of a Function |
influence.ppm | Influence Measure for Spatial Point Process Model |
influence.slrm | Leverage and Influence Diagnostics for Spatial Logistic Regression |
inforder.family | Infinite Order Interaction Family |
integral.influence.ppm | Methods for Influence Objects |
integral.leverage.ppm | Methods for Leverage Objects |
integral.msr | Integral of a Measure |
integral.ssf | Methods for Spatially Sampled Functions |
intensity.detpointprocfamily | Intensity of Determinantal Point Process Model |
intensity.dppm | Intensity of Determinantal Point Process Model |
intensity.ppm | Intensity of Fitted Point Process Model |
intensity.slrm | Intensity of Fitted Spatial Logistic Regression Model |
intensity.zclustermodel | Methods for Cluster Models |
intensity.zgibbsmodel | Methods for Gibbs Models |
interactionorder | Determine the Order of Interpoint Interaction in a Model |
interactionorder.fii | Determine the Order of Interpoint Interaction in a Model |
interactionorder.interact | Determine the Order of Interpoint Interaction in a Model |
interactionorder.isf | Determine the Order of Interpoint Interaction in a Model |
interactionorder.ppm | Determine the Order of Interpoint Interaction in a Model |
interactionorder.zgibbsmodel | Methods for Gibbs Models |
ippm | Fit Point Process Model Involving Irregular Trend Parameters |
is.dppm | Recognise Fitted Determinantal Point Process Models |
is.hybrid | Test Whether Object is a Hybrid |
is.hybrid.interact | Test Whether Object is a Hybrid |
is.hybrid.ppm | Test Whether Object is a Hybrid |
is.kppm | Test Whether An Object Is A Fitted Point Process Model |
is.lppm | Test Whether An Object Is A Fitted Point Process Model |
is.marked.ppm | Test Whether A Point Process Model is Marked |
is.multitype.ppm | Test Whether A Point Process Model is Multitype |
is.poisson.interact | Recognise Stationary and Poisson Point Process Models |
is.poisson.kppm | Recognise Stationary and Poisson Point Process Models |
is.poisson.ppm | Recognise Stationary and Poisson Point Process Models |
is.poisson.slrm | Recognise Stationary and Poisson Point Process Models |
is.poisson.zgibbsmodel | Methods for Gibbs Models |
is.ppm | Test Whether An Object Is A Fitted Point Process Model |
is.slrm | Test Whether An Object Is A Fitted Point Process Model |
is.stationary.detpointprocfamily | Recognise Stationary and Poisson Point Process Models |
is.stationary.dppm | Recognise Stationary and Poisson Point Process Models |
is.stationary.kppm | Recognise Stationary and Poisson Point Process Models |
is.stationary.ppm | Recognise Stationary and Poisson Point Process Models |
is.stationary.slrm | Recognise Stationary and Poisson Point Process Models |
is.stationary.zgibbsmodel | Methods for Gibbs Models |
isf.object | Interaction Structure Family Objects |
Jcross | Multitype J Function (i-to-j) |
Jdot | Multitype J Function (i-to-any) |
Jest | Estimate the J-function |
Jfox | Foxall's Distance Functions |
Jinhom | Inhomogeneous J-function |
Jmulti | Marked J Function |
K3est | K-function of a Three-Dimensional Point Pattern |
kaplan.meier | Kaplan-Meier Estimator using Histogram Data |
Kcom | Model Compensator of K Function |
Kcross | Multitype K Function (Cross-type) |
Kcross.inhom | Inhomogeneous Cross K Function |
Kdot | Multitype K Function (i-to-any) |
Kdot.inhom | Inhomogeneous Multitype K Dot Function |
kernel.factor | Scale factor for density kernel |
kernel.moment | Moment of Smoothing Kernel |
kernel.squint | Integral of Squared Kernel |
Kest | K-function |
Kest.fft | K-function using FFT |
Kinhom | Inhomogeneous K-function |
km.rs | Kaplan-Meier and Reduced Sample Estimator using Histograms |
Kmark | Mark-Weighted K Function |
Kmeasure | Reduced Second Moment Measure |
Kmodel | K Function or Pair Correlation Function of a Point Process Model |
Kmodel.detpointprocfamily | K-function or Pair Correlation Function of a Determinantal Point Process Model |
Kmodel.dppm | K-function or Pair Correlation Function of a Determinantal Point Process Model |
Kmodel.kppm | K Function or Pair Correlation Function of Cluster Model or Cox model |
Kmodel.ppm | K Function or Pair Correlation Function of Gibbs Point Process model |
Kmodel.zclustermodel | Methods for Cluster Models |
Kmulti | Marked K-Function |
Kmulti.inhom | Inhomogeneous Marked K-Function |
kppm | Fit Cluster or Cox Point Process Model |
kppm.formula | Fit Cluster or Cox Point Process Model |
kppm.ppp | Fit Cluster or Cox Point Process Model |
kppm.quad | Fit Cluster or Cox Point Process Model |
Kres | Residual K Function |
Kscaled | Locally Scaled K-function |
Ksector | Sector K-function |
labels.dppm | Methods for Determinantal Point Process Models |
labels.kppm | Methods for Cluster Point Process Models |
labels.slrm | Methods for Spatial Logistic Regression Models |
LambertW | Lambert's W Function |
laslett | Laslett's Transform |
Lcross | Multitype L-function (cross-type) |
Lcross.inhom | Inhomogeneous Cross Type L Function |
Ldot | Multitype L-function (i-to-any) |
Ldot.inhom | Inhomogeneous Multitype L Dot Function |
LennardJones | The Lennard-Jones Potential |
Lest | L-function |
leverage | Leverage Measure for Spatial Point Process Model |
leverage.ppm | Leverage Measure for Spatial Point Process Model |
leverage.slrm | Leverage and Influence Diagnostics for Spatial Logistic Regression |
lgcp.estK | Fit a Log-Gaussian Cox Point Process by Minimum Contrast |
lgcp.estpcf | Fit a Log-Gaussian Cox Point Process by Minimum Contrast |
Linhom | Inhomogeneous L-function |
localK | Neighbourhood density function |
localKcross | Local Multitype K Function (Cross-Type) |
localKcross.inhom | Inhomogeneous Multitype K Function |
localKdot | Local Multitype K Function (Dot-Type) |
localKinhom | Inhomogeneous Neighbourhood Density Function |
localL | Neighbourhood density function |
localLcross | Local Multitype K Function (Cross-Type) |
localLcross.inhom | Inhomogeneous Multitype K Function |
localLdot | Local Multitype K Function (Dot-Type) |
localLinhom | Inhomogeneous Neighbourhood Density Function |
localpcf | Local pair correlation function |
localpcfinhom | Local pair correlation function |
logLik.dppm | Log Likelihood and AIC for Fitted Determinantal Point Process Model |
logLik.kppm | Log Likelihood and AIC for Fitted Cox or Cluster Point Process Model |
logLik.mppm | Log Likelihood and AIC for Multiple Point Process Model |
logLik.ppm | Log Likelihood and AIC for Point Process Model |
logLik.slrm | Loglikelihood of Spatial Logistic Regression |
lohboot | Bootstrap Confidence Bands for Summary Function |
Lscaled | Locally Scaled K-function |
lurking | Lurking Variable Plot |
lurking.mppm | Lurking Variable Plot for Multiple Point Patterns |
lurking.ppm | Lurking Variable Plot |
lurking.ppp | Lurking Variable Plot |
mad.progress | Progress Plot of Test of Spatial Pattern |
mad.sigtrace | Significance Trace of Cressie-Loosmore-Ford or Maximum Absolute Deviation Test |
mad.test | Diggle-Cressie-Loosmore-Ford and Maximum Absolute Deviation Tests |
markconnect | Mark Connection Function |
markcorr | Mark Correlation Function |
markcorrint | Mark-Weighted K Function |
markcrosscorr | Mark Cross-Correlation Function |
markmarkscatter | Mark-Mark Scatter Plot |
markmean | Spatial smoothing of observations at irregular points |
marks.ssf | Methods for Spatially Sampled Functions |
marks<-.ssf | Methods for Spatially Sampled Functions |
marktable | Tabulate Marks in Neighbourhood of Every Point in a Point Pattern |
markvar | Spatial smoothing of observations at irregular points |
markvario | Mark Variogram |
matclust.estK | Fit the Matern Cluster Point Process by Minimum Contrast |
matclust.estpcf | Fit the Matern Cluster Point Process by Minimum Contrast Using Pair Correlation |
max.fv | Range of Function Values |
max.ssf | Methods for Spatially Sampled Functions |
mctest.progress | Progress Plot of Test of Spatial Pattern |
mctest.sigtrace | Significance Trace of Cressie-Loosmore-Ford or Maximum Absolute Deviation Test |
mean.leverage.ppm | Methods for Leverage Objects |
measureContinuous | Discrete and Continuous Components of a Measure |
measureDiscrete | Discrete and Continuous Components of a Measure |
measureNegative | Positive and Negative Parts, and Variation, of a Measure |
measurePositive | Positive and Negative Parts, and Variation, of a Measure |
measureVariation | Positive and Negative Parts, and Variation, of a Measure |
methods.dppm | Methods for Determinantal Point Process Models |
methods.fii | Methods for Fitted Interactions |
methods.influence.ppm | Methods for Influence Objects |
methods.kppm | Methods for Cluster Point Process Models |
methods.leverage.ppm | Methods for Leverage Objects |
methods.objsurf | Methods for Objective Function Surfaces |
methods.ppm | Class of Fitted Point Process Models |
methods.rho2hat | Methods for Intensity Functions of Two Spatial Covariates |
methods.rhohat | Methods for Intensity Functions of Spatial Covariate |
methods.slrm | Methods for Spatial Logistic Regression Models |
methods.ssf | Methods for Spatially Sampled Functions |
methods.zclustermodel | Methods for Cluster Models |
methods.zgibbsmodel | Methods for Gibbs Models |
min.fv | Range of Function Values |
min.ssf | Methods for Spatially Sampled Functions |
mincontrast | Method of Minimum Contrast |
miplot | Morisita Index Plot |
model.covariates | Identify Covariates Involved in each Model Term |
model.depends | Identify Covariates Involved in each Model Term |
model.frame.dppm | Extract the Variables in a Point Process Model |
model.frame.kppm | Extract the Variables in a Point Process Model |
model.frame.ppm | Extract the Variables in a Point Process Model |
model.frame.slrm | Extract the Variables in a Point Process Model |
model.images | Compute Images of Constructed Covariates |
model.images.dppm | Compute Images of Constructed Covariates |
model.images.kppm | Compute Images of Constructed Covariates |
model.images.ppm | Compute Images of Constructed Covariates |
model.images.slrm | Compute Images of Constructed Covariates |
model.is.additive | Identify Covariates Involved in each Model Term |
model.matrix.dppm | Extract Design Matrix from Point Process Model |
model.matrix.ippm | Extract Design Matrix from Point Process Model |
model.matrix.kppm | Extract Design Matrix from Point Process Model |
model.matrix.mppm | Extract Design Matrix of Point Process Model for Several Point Patterns |
model.matrix.ppm | Extract Design Matrix from Point Process Model |
model.matrix.slrm | Extract Design Matrix from Spatial Logistic Regression Model |
mppm | Fit Point Process Model to Several Point Patterns |
msr | Signed or Vector-Valued Measure |
MultiHard | The Multitype Hard Core Point Process Model |
MultiStrauss | The Multitype Strauss Point Process Model |
MultiStraussHard | The Multitype/Hard Core Strauss Point Process Model |
nearest.neighbour | Nearest Neighbour Distance Function G |
nnclean | Nearest Neighbour Clutter Removal |
nnclean.pp3 | Nearest Neighbour Clutter Removal |
nnclean.ppp | Nearest Neighbour Clutter Removal |
nncorr | Nearest-Neighbour Correlation Indices of Marked Point Pattern |
nndensity | Estimate Intensity of Point Pattern Using Nearest Neighbour Distances |
nndensity.ppp | Estimate Intensity of Point Pattern Using Nearest Neighbour Distances |
nnmean | Nearest-Neighbour Correlation Indices of Marked Point Pattern |
nnorient | Nearest Neighbour Orientation Distribution |
nnvario | Nearest-Neighbour Correlation Indices of Marked Point Pattern |
nobs.dppm | Log Likelihood and AIC for Fitted Determinantal Point Process Model |
nobs.kppm | Log Likelihood and AIC for Fitted Cox or Cluster Point Process Model |
nobs.mppm | Log Likelihood and AIC for Multiple Point Process Model |
nobs.ppm | Log Likelihood and AIC for Point Process Model |
npfun | Dummy Function Returns Number of Points |
objsurf | Objective Function Surface |
objsurf.dppm | Objective Function Surface |
objsurf.kppm | Objective Function Surface |
objsurf.minconfit | Objective Function Surface |
Ops.msr | Arithmetic Operations on Measures |
Ord | Generic Ord Interaction model |
ord.family | Ord Interaction Process Family |
OrdThresh | Ord's Interaction model |
pairMean | Mean of a Function of Interpoint Distance |
pairorient | Point Pair Orientation Distribution |
PairPiece | The Piecewise Constant Pairwise Interaction Point Process Model |
pairs.im | Scatterplot Matrix for Pixel Images |
pairsat.family | Saturated Pairwise Interaction Point Process Family |
Pairwise | Generic Pairwise Interaction model |
pairwise.family | Pairwise Interaction Process Family |
panel.contour | Panel Plots using Colour Image or Contour Lines |
panel.histogram | Panel Plots using Colour Image or Contour Lines |
panel.image | Panel Plots using Colour Image or Contour Lines |
parameters | Extract Model Parameters in Understandable Form |
parameters.dppm | Extract Model Parameters in Understandable Form |
parameters.fii | Extract Model Parameters in Understandable Form |
parameters.interact | Extract Model Parameters in Understandable Form |
parameters.kppm | Extract Model Parameters in Understandable Form |
parameters.ppm | Extract Model Parameters in Understandable Form |
parameters.profilepl | Extract Model Parameters in Understandable Form |
parameters.slrm | Extract Model Parameters in Understandable Form |
parres | Partial Residuals for Point Process Model |
pcf | Pair Correlation Function |
pcf.fasp | Pair Correlation Function obtained from array of K functions |
pcf.fv | Pair Correlation Function obtained from K Function |
pcf.ppp | Pair Correlation Function of Point Pattern |
pcf3est | Pair Correlation Function of a Three-Dimensional Point Pattern |
pcfcross | Multitype pair correlation function (cross-type) |
pcfcross.inhom | Inhomogeneous Multitype Pair Correlation Function (Cross-Type) |
pcfdot | Multitype pair correlation function (i-to-any) |
pcfdot.inhom | Inhomogeneous Multitype Pair Correlation Function (Type-i-To-Any-Type) |
pcfinhom | Inhomogeneous Pair Correlation Function |
pcfmodel | K Function or Pair Correlation Function of a Point Process Model |
pcfmodel.detpointprocfamily | K-function or Pair Correlation Function of a Determinantal Point Process Model |
pcfmodel.dppm | K-function or Pair Correlation Function of a Determinantal Point Process Model |
pcfmodel.kppm | K Function or Pair Correlation Function of Cluster Model or Cox model |
pcfmodel.ppm | K Function or Pair Correlation Function of Gibbs Point Process model |
pcfmodel.zclustermodel | Methods for Cluster Models |
pcfmulti | Marked pair correlation function |
Penttinen | Penttinen Interaction |
persp.leverage.ppm | Plot Leverage Function |
persp.objsurf | Methods for Objective Function Surfaces |
pkernel | Kernel distributions and random generation |
plot.bermantest | Plot Result of Berman Test |
plot.cdftest | Plot a Spatial Distribution Test |
plot.diagppm | Diagnostic Plots for Fitted Point Process Model |
plot.dppm | Plot a fitted determinantal point process |
plot.envelope | Plot a Simulation Envelope |
plot.fasp | Plot a Function Array |
plot.fii | Methods for Fitted Interactions |
plot.fv | Plot Function Values |
plot.influence.ppm | Plot Influence Measure |
plot.kppm | Plot a fitted cluster point process |
plot.laslett | Plot Laslett Transform |
plot.leverage.ppm | Plot Leverage Function |
plot.mppm | plot a Fitted Multiple Point Process Model |
plot.msr | Plot a Signed or Vector-Valued Measure |
plot.objsurf | Methods for Objective Function Surfaces |
plot.plotppm | Plot a plotppm Object Created by plot.ppm |
plot.ppm | plot a Fitted Point Process Model |
plot.profilepl | Plot Profile Likelihood |
plot.quadrattest | Display the result of a quadrat counting test. |
plot.rho2hat | Methods for Intensity Functions of Two Spatial Covariates |
plot.rhohat | Methods for Intensity Functions of Spatial Covariate |
plot.rppm | Plot a Recursively Partitioned Point Process Model |
plot.scan.test | Plot Result of Scan Test |
plot.slrm | Plot a Fitted Spatial Logistic Regression |
plot.ssf | Plot a Spatially Sampled Function |
plot.studpermutest | Plot a Studentised Permutation Test |
Poisson | Poisson Point Process Model |
polynom | Polynomial in One or Two Variables |
pool | Pool Data |
pool.anylist | Pool Data from a List of Objects |
pool.envelope | Pool Data from Several Envelopes |
pool.fasp | Pool Data from Several Function Arrays |
pool.fv | Pool Several Functions |
pool.quadrattest | Pool Several Quadrat Tests |
pool.rat | Pool Data from Several Ratio Objects |
ppm | Fit Point Process Model to Data |
ppm.formula | Fit Point Process Model to Data |
ppm.object | Class of Fitted Point Process Models |
ppm.ppp | Fit Point Process Model to Point Pattern Data |
ppm.quad | Fit Point Process Model to Point Pattern Data |
ppmInfluence | Leverage and Influence Measures for Spatial Point Process Model |
PPversion | Transform a Function into its P-P or Q-Q Version |
predict.dppm | Prediction from a Fitted Determinantal Point Process Model |
predict.kppm | Prediction from a Fitted Cluster Point Process Model |
predict.mppm | Prediction for Fitted Multiple Point Process Model |
predict.ppm | Prediction from a Fitted Point Process Model |
predict.rho2hat | Methods for Intensity Functions of Two Spatial Covariates |
predict.rhohat | Methods for Intensity Functions of Spatial Covariate |
predict.rppm | Make Predictions From a Recursively Partitioned Point Process Model |
predict.slrm | Predicted or Fitted Values from Spatial Logistic Regression |
predict.zclustermodel | Methods for Cluster Models |
print.dppm | Methods for Determinantal Point Process Models |
print.fii | Methods for Fitted Interactions |
print.kppm | Methods for Cluster Point Process Models |
print.objsurf | Methods for Objective Function Surfaces |
print.ppm | Print a Fitted Point Process Model |
print.rho2hat | Methods for Intensity Functions of Two Spatial Covariates |
print.rhohat | Methods for Intensity Functions of Spatial Covariate |
print.slrm | Methods for Spatial Logistic Regression Models |
print.ssf | Methods for Spatially Sampled Functions |
print.summary.dppm | Summarizing a Fitted Determinantal Point Process Model |
print.summary.fii | Methods for Fitted Interactions |
print.summary.kppm | Summarizing a Fitted Cox or Cluster Point Process Model |
print.summary.objsurf | Methods for Objective Function Surfaces |
print.summary.ppm | Summarizing a Fitted Point Process Model |
print.zclustermodel | Methods for Cluster Models |
print.zgibbsmodel | Methods for Gibbs Models |
profilepl | Fit Models by Profile Maximum Pseudolikelihood or AIC |
project.ppm | Force Point Process Model to be Valid |
prune.rppm | Prune a Recursively Partitioned Point Process Model |
pseudoR2 | Calculate Pseudo-R-Squared for Point Process Model |
pseudoR2.ppm | Calculate Pseudo-R-Squared for Point Process Model |
pseudoR2.slrm | Calculate Pseudo-R-Squared for Point Process Model |
psib | Sibling Probability of Cluster Point Process |
psib.kppm | Sibling Probability of Cluster Point Process |
psst | Pseudoscore Diagnostic For Fitted Model against General Alternative |
psstA | Pseudoscore Diagnostic For Fitted Model against Area-Interaction Alternative |
psstG | Pseudoscore Diagnostic For Fitted Model against Saturation Alternative |
qkernel | Kernel distributions and random generation |
qqplot.ppm | Q-Q Plot of Residuals from Fitted Point Process Model |
QQversion | Transform a Function into its P-P or Q-Q Version |
quad.ppm | Extract Quadrature Scheme Used to Fit a Point Process Model |
quadrat.test | Dispersion Test for Spatial Point Pattern Based on Quadrat Counts |
quadrat.test.mppm | Chi-Squared Test for Multiple Point Process Model Based on Quadrat Counts |
quadrat.test.ppm | Dispersion Test for Spatial Point Pattern Based on Quadrat Counts |
quadrat.test.ppp | Dispersion Test for Spatial Point Pattern Based on Quadrat Counts |
quadrat.test.quadratcount | Dispersion Test for Spatial Point Pattern Based on Quadrat Counts |
quadrat.test.slrm | Dispersion Test for Spatial Point Pattern Based on Quadrat Counts |
quadrat.test.splitppp | Dispersion Test of CSR for Split Point Pattern Based on Quadrat Counts |
quantile.density | Quantiles of a Density Estimate |
ranef.mppm | Extract Random Effects from Point Process Model |
range.fv | Range of Function Values |
range.ssf | Methods for Spatially Sampled Functions |
rat | Ratio object |
rdpp | Simulation of a Determinantal Point Process |
reach.detpointprocfamily | Range of Interaction for a Determinantal Point Process Model |
reach.dppm | Range of Interaction for a Determinantal Point Process Model |
reach.fii | Interaction Distance of a Point Process Model |
reach.interact | Interaction Distance of a Point Process Model |
reach.kppm | Range of Interaction for a Cox or Cluster Point Process Model |
reach.ppm | Interaction Distance of a Point Process Model |
reach.zclustermodel | Methods for Cluster Models |
rectcontact | Contact Distribution Function using Rectangular Structuring Element |
reduced.sample | Reduced Sample Estimator using Histogram Data |
reload.or.compute | Compute Unless Previously Saved |
relrisk | Estimate of Spatially-Varying Relative Risk |
relrisk.ppm | Parametric Estimate of Spatially-Varying Relative Risk |
relrisk.ppp | Nonparametric Estimate of Spatially-Varying Relative Risk |
repul | Repulsiveness Index of a Determinantal Point Process Model |
repul.dppm | Repulsiveness Index of a Determinantal Point Process Model |
residuals.dppm | Residuals for Fitted Determinantal Point Process Model |
residuals.kppm | Residuals for Fitted Cox or Cluster Point Process Model |
residuals.mppm | Residuals for Point Process Model Fitted to Multiple Point Patterns |
residuals.ppm | Residuals for Fitted Point Process Model |
residuals.slrm | Residuals for Fitted Spatial Logistic Regression Model |
response | Extract the Values of the Response from a Fitted Model |
response.dppm | Extract the Values of the Response from a Fitted Model |
response.glm | Extract the Values of the Response from a Fitted Model |
response.kppm | Extract the Values of the Response from a Fitted Model |
response.lm | Extract the Values of the Response from a Fitted Model |
response.mppm | Extract the Values of the Response from a Fitted Model |
response.ppm | Extract the Values of the Response from a Fitted Model |
response.slrm | Extract the Values of the Response from a Fitted Model |
rex | Richardson Extrapolation |
rho2hat | Smoothed Relative Density of Pairs of Covariate Values |
rhohat | Nonparametric Estimate of Intensity as Function of a Covariate |
rhohat.ppm | Nonparametric Estimate of Intensity as Function of a Covariate |
rhohat.ppp | Nonparametric Estimate of Intensity as Function of a Covariate |
rhohat.quad | Nonparametric Estimate of Intensity as Function of a Covariate |
rhohat.slrm | Nonparametric Estimate of Intensity as Function of a Covariate |
rkernel | Kernel distributions and random generation |
rmax.Ripley | Ripley's Isotropic Edge Correction |
rmax.Trans | Translation Edge Correction |
rmh.ppm | Simulate from a Fitted Point Process Model |
rmhmodel.ppm | Interpret Fitted Model for Metropolis-Hastings Simulation. |
roc | Receiver Operating Characteristic |
roc.kppm | Receiver Operating Characteristic |
roc.ppm | Receiver Operating Characteristic |
roc.ppp | Receiver Operating Characteristic |
roc.slrm | Receiver Operating Characteristic |
rose | Rose Diagram |
rose.default | Rose Diagram |
rose.density | Rose Diagram |
rose.fv | Rose Diagram |
rose.histogram | Rose Diagram |
rotmean | Rotational Average of a Pixel Image |
rppm | Recursively Partitioned Point Process Model |
SatPiece | Piecewise Constant Saturated Pairwise Interaction Point Process Model |
Saturated | Saturated Pairwise Interaction model |
scan.test | Spatial Scan Test |
scanLRTS | Likelihood Ratio Test Statistic for Scan Test |
sdr | Sufficient Dimension Reduction |
sdr.ppp | Sufficient Dimension Reduction |
sdrPredict | Compute Predictors from Sufficient Dimension Reduction |
segregation.test | Test of Spatial Segregation of Types |
segregation.test.ppp | Test of Spatial Segregation of Types |
sharpen | Data Sharpening of Point Pattern |
sharpen.ppp | Data Sharpening of Point Pattern |
simulate.detpointprocfamily | Simulation of Determinantal Point Process Model |
simulate.dppm | Simulation of Determinantal Point Process Model |
simulate.kppm | Simulate a Fitted Cluster Point Process Model |
simulate.mppm | Simulate a Point Process Model Fitted to Several Point Patterns |
simulate.ppm | Simulate a Fitted Gibbs Point Process Model |
simulate.rhohat | Methods for Intensity Functions of Spatial Covariate |
simulate.slrm | Simulate a Fitted Spatial Logistic Regression Model |
slrm | Spatial Logistic Regression |
Smooth | Spatial smoothing of data |
Smooth.fv | Apply Smoothing to Function Values |
Smooth.im | Apply Gaussian Blur to a Pixel Image |
Smooth.influence.ppm | Methods for Influence Objects |
Smooth.leverage.ppm | Methods for Leverage Objects |
Smooth.msr | Smooth a Signed or Vector-Valued Measure |
Smooth.ppp | Spatial smoothing of observations at irregular points |
Smooth.ssf | Smooth a Spatially Sampled Function |
Smoothfun | Smooth Interpolation of Marks as a Spatial Function |
Smoothfun.ppp | Smooth Interpolation of Marks as a Spatial Function |
Softcore | The Soft Core Point Process Model |
spatcov | Estimate the Spatial Covariance Function of a Random Field |
spatialcdf | Spatial Cumulative Distribution Function |
spatstat.core | The spatstat.core Package |
split.msr | Divide a Measure into Parts |
ssf | Spatially Sampled Function |
stieltjes | Compute Integral of Function Against Cumulative Distribution |
stienen | Stienen Diagram |
stienenSet | Stienen Diagram |
Strauss | The Strauss Point Process Model |
StraussHard | The Strauss / Hard Core Point Process Model |
studpermu.test | Studentised Permutation Test |
subfits | Extract List of Individual Point Process Models |
subfits.new | Extract List of Individual Point Process Models |
subfits.old | Extract List of Individual Point Process Models |
subspaceDistance | Distance Between Linear Spaces |
suffstat | Sufficient Statistic of Point Process Model |
summary.dppm | Summarizing a Fitted Determinantal Point Process Model |
summary.fii | Methods for Fitted Interactions |
summary.kppm | Summarizing a Fitted Cox or Cluster Point Process Model |
summary.objsurf | Methods for Objective Function Surfaces |
summary.ppm | Summarizing a Fitted Point Process Model |
summary.slrm | Methods for Spatial Logistic Regression Models |
summary.ssf | Methods for Spatially Sampled Functions |
terms.dppm | Methods for Determinantal Point Process Models |
terms.kppm | Methods for Cluster Point Process Models |
terms.mppm | Log Likelihood and AIC for Multiple Point Process Model |
terms.ppm | Model Formulae for Gibbs Point Process Models |
terms.slrm | Methods for Spatial Logistic Regression Models |
thomas.estK | Fit the Thomas Point Process by Minimum Contrast |
thomas.estpcf | Fit the Thomas Point Process by Minimum Contrast |
thresholdCI | Confidence Interval for Threshold of Numerical Predictor |
thresholdSelect | Select Threshold to Convert Numerical Predictor to Binary Predictor |
totalVariation | Positive and Negative Parts, and Variation, of a Measure |
transect.im | Pixel Values Along a Transect |
triplet.family | Triplet Interaction Family |
Triplets | The Triplet Point Process Model |
Tstat | Third order summary statistic |
unitname.dppm | Name for Unit of Length |
unitname.kppm | Name for Unit of Length |
unitname.minconfit | Name for Unit of Length |
unitname.ppm | Name for Unit of Length |
unitname.slrm | Name for Unit of Length |
unitname<-.dppm | Name for Unit of Length |
unitname<-.kppm | Name for Unit of Length |
unitname<-.minconfit | Name for Unit of Length |
unitname<-.ppm | Name for Unit of Length |
unitname<-.slrm | Name for Unit of Length |
unmark.ssf | Methods for Spatially Sampled Functions |
unstack.msr | Separate a Vector Measure into its Scalar Components |
update.detpointprocfamily | Set Parameter Values in a Determinantal Point Process Model |
update.interact | Update an Interpoint Interaction |
update.kppm | Update a Fitted Cluster Point Process Model |
update.ppm | Update a Fitted Point Process Model |
update.slrm | Methods for Spatial Logistic Regression Models |
valid | Check Whether Point Process Model is Valid |
valid.detpointprocfamily | Check Validity of a Determinantal Point Process Model |
valid.ppm | Check Whether Point Process Model is Valid |
valid.slrm | Check Whether Spatial Logistic Regression Model is Valid |
varblock | Estimate Variance of Summary Statistic by Subdivision |
varcount | Predicted Variance of the Number of Points |
vargamma.estK | Fit the Neyman-Scott Cluster Point Process with Variance Gamma kernel |
vargamma.estpcf | Fit the Neyman-Scott Cluster Point Process with Variance Gamma kernel |
vcov.kppm | Variance-Covariance Matrix for a Fitted Cluster Point Process Model |
vcov.mppm | Calculate Variance-Covariance Matrix for Fitted Multiple Point Process Model |
vcov.ppm | Variance-Covariance Matrix for a Fitted Point Process Model |
vcov.slrm | Variance-Covariance Matrix for a Fitted Spatial Logistic Regression |
Vmark | Diagnostics for random marking |
Window.dppm | Extract Window of Spatial Object |
Window.influence.ppm | Methods for Influence Objects |
Window.kppm | Extract Window of Spatial Object |
Window.leverage.ppm | Methods for Leverage Objects |
Window.msr | Extract Window of Spatial Object |
Window.ppm | Extract Window of Spatial Object |
Window.quadrattest | Extract Window of Spatial Object |
Window.slrm | Extract Window of Spatial Object |
with.fv | Evaluate an Expression in a Function Table |
with.msr | Evaluate Expression Involving Components of a Measure |
with.ssf | Evaluate Expression in a Spatially Sampled Function |
zclustermodel | Cluster Point Process Model |
zgibbsmodel | Gibbs Model |
$<-.fv | Extract or Replace Subset of Function Values |
[.fasp | Extract Subset of Function Array |
[.fv | Extract or Replace Subset of Function Values |
[.influence.ppm | Extract Subset of Influence Object |
[.leverage.ppm | Extract Subset of Leverage Object |
[.msr | Extract Subset of Signed or Vector Measure |
[.ssf | Subset of spatially sampled function |
[<-.fv | Extract or Replace Subset of Function Values |