R: Parametric Statistical Modelling and Inference for the 'spatstat' Family

# Parametric Statistical Modelling and Inference for the 'spatstat' Family

## Documentation for package ‘spatstat.model’ version 3.3-4

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

A B C D E F G H I K L M N O P Q R S T U V W Z misc

spatstat.model-package | The spatstat.model Package

## -- A --

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
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
AreaInter | The Area Interaction Point Process Model
as.function.leverage.ppm | Convert Leverage Object to Function of Coordinates
as.fv.dppm | Convert Fitted Model To Class fv
as.fv.kppm | Convert Fitted Model To Class fv
as.fv.minconfit | Convert Fitted Model To Class fv
as.im.leverage.ppm | Methods for Leverage Objects
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.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.ppm.rppm | Extract Fitted Point Process Model
as.ppp.influence.ppm | Methods for Influence Objects
auc.kppm | Area Under ROC Curve
auc.ppm | Area Under ROC Curve
auc.slrm | Area Under ROC Curve

## -- B --

BadGey | Hybrid Geyer Point Process Model
bc | Bias Correction for Fitted Model
bc.ppm | Bias Correction for Fitted Model
berman.test.ppm | Berman's Tests for Point Process Model

## -- C --

cauchy.estK | Fit the Neyman-Scott cluster process with Cauchy kernel
cauchy.estpcf | Fit the Neyman-Scott cluster process with Cauchy kernel
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.slrm | Spatial Distribution Test for Point Pattern or Point Process Model
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
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
compareFit | Residual Diagnostics for Multiple Fitted Models
Concom | The Connected Component Process Model
contour.leverage.ppm | Plot Leverage Function
contour.objsurf | Methods for Objective Function Surfaces
crosspaircounts | Count Close Pairs of Points

## -- D --

data.ppm | Extract Original Data from a Fitted Point Process Model
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
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
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.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

## -- E --

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
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.kppm | Simulation Envelopes of Summary Function
envelope.ppm | Simulation Envelopes of Summary Function
envelope.slrm | Simulation Envelopes of Summary Function
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

## -- F --

Fiksel | The Fiksel Interaction
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
formula.dppm | Methods for Determinantal Point Process Models
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

## -- G --

Gcom | Model Compensator of Nearest Neighbour Function
getCall.mppm | Log Likelihood and AIC for Multiple Point Process Model
Geyer | Geyer's Saturation Point Process Model
Gres | Residual G Function

## -- H --

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.msr | Make Measures Compatible
has.offset | Identify Covariates Involved in each Model Term
has.offset.term | Identify Covariates Involved in each Model Term
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
Hybrid | Hybrid Interaction Point Process Model
hybrid.family | Hybrid Interaction Family

## -- I --

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
image.objsurf | Methods for Objective Function Surfaces
improve.kppm | Improve Intensity Estimate of Fitted Cluster Point Process Model
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
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.poissonclusterprocess | Recognise Poisson Cluster Process Models
is.poissonclusterprocess.default | Recognise Poisson Cluster Process Models
is.poissonclusterprocess.kppm | Recognise Poisson Cluster Process Models
is.poissonclusterprocess.zclustermodel | Recognise Poisson Cluster Process 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

## -- K --

Kcom | Model Compensator of K Function
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
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

## -- L --

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
LennardJones | The Lennard-Jones Potential
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
lines.traj | Methods for Trajectories of Function Evaluations
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
lurking | Lurking Variable Plot
lurking.mppm | Lurking Variable Plot for Multiple Point Patterns
lurking.ppm | Lurking Variable Plot
lurking.ppp | Lurking Variable Plot

## -- M --

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
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
measureWeighted | Weighted Version 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.slrm | Methods for Spatial Logistic Regression Models
methods.traj | Methods for Trajectories of Function Evaluations
methods.zclustermodel | Methods for Cluster Models
methods.zgibbsmodel | Methods for Gibbs Models
mincontrast | Method of Minimum Contrast
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

## -- N --

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

## -- O --

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

## -- P --

PairPiece | The Piecewise Constant Pairwise Interaction Point Process Model
pairsat.family | Saturated Pairwise Interaction Point Process Family
Pairwise | Generic Pairwise Interaction model
pairwise.family | Pairwise Interaction Process Family
palmdiagnose | Diagnostic based on Palm Intensity
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
panysib | Probability that a Point Has Any Siblings
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
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
Penttinen | Penttinen Interaction
persp.leverage.ppm | Plot Leverage Function
persp.objsurf | Methods for Objective Function Surfaces
plot.diagppm | Diagnostic Plots for Fitted Point Process Model
plot.dppm | Plot a fitted determinantal point process
plot.fii | Methods for Fitted Interactions
plot.influence.ppm | Plot Influence Measure
plot.kppm | Plot a fitted cluster point process
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.palmdiag | Plot the Palm Intensity Diagnostic
plot.plotppm | Plot a plotppm Object Created by plot.ppm
plot.ppm | plot a Fitted Point Process Model
plot.profilepl | Plot Profile Likelihood
plot.rppm | Plot a Recursively Partitioned Point Process Model
plot.slrm | Plot a Fitted Spatial Logistic Regression
plot.traj | Methods for Trajectories of Function Evaluations
Poisson | Poisson Point Process Model
polynom | Polynomial in One or Two Variables
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
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.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.slrm | Methods for Spatial Logistic Regression Models
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.traj | Methods for Trajectories of Function Evaluations
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

## -- Q --

qqplot.ppm | Q-Q Plot of Residuals from Fitted Point Process Model
quad.ppm | Extract Quadrature Scheme Used to Fit a Point Process Model
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.slrm | Dispersion Test for Spatial Point Pattern Based on Quadrat Counts

## -- R --

ranef.mppm | Extract Random Effects from Point Process Model
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
relrisk.ppm | Parametric 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
residualMeasure | Residual Measure for an Observed Point Pattern and a Fitted Intensity
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.rppm | Residuals for Recursively Partitioned 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.rppm | 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
rhohat.ppm | Nonparametric Estimate of Intensity as Function of a Covariate
rhohat.slrm | Nonparametric Estimate of Intensity as Function of a Covariate
rmh.ppm | Simulate from a Fitted Point Process Model
rmhmodel.ppm | Interpret Fitted Model for Metropolis-Hastings Simulation.
roc.kppm | Receiver Operating Characteristic
roc.ppm | Receiver Operating Characteristic
roc.slrm | Receiver Operating Characteristic
rppm | Recursively Partitioned Point Process Model

## -- S --

SatPiece | Piecewise Constant Saturated Pairwise Interaction Point Process Model
Saturated | Saturated Pairwise Interaction model
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.slrm | Simulate a Fitted Spatial Logistic Regression Model
slrm | Spatial Logistic Regression
Smooth.influence.ppm | Methods for Influence Objects
Smooth.leverage.ppm | Methods for Leverage Objects
Smooth.msr | Smooth a Signed or Vector-Valued Measure
Softcore | The Soft Core Point Process Model
spatstat.model | The spatstat.model Package
split.msr | Divide a Measure into Parts
Strauss | The Strauss Point Process Model
StraussHard | The Strauss / Hard Core Point Process Model
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
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

## -- T --

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
totalVariation | Positive and Negative Parts, and Variation, of a Measure
traj | Extract trajectory of function evaluations
triplet.family | Triplet Interaction Family
Triplets | The Triplet Point Process Model

## -- U --

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
unstack.msr | Separate a Vector Measure into its Scalar Components
update.detpointprocfamily | Set Parameter Values in a Determinantal Point Process Model
update.dppm | Update a Fitted 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.rppm | Update a Recursively Partitioned Point Process Model
update.slrm | Methods for Spatial Logistic Regression Models

## -- V --

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
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

## -- W --

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.slrm | Extract Window of Spatial Object
with.msr | Evaluate Expression Involving Components of a Measure

## -- Z --

zclustermodel | Cluster Point Process Model
zgibbsmodel | Gibbs Model

## -- misc --

[.influence.ppm | Extract Subset of Influence Object
[.leverage.ppm | Extract Subset of Leverage Object
[.msr | Extract Subset of Signed or Vector Measure