Conway-Maxwell-Poisson (COM-Poisson) GLM family
Fits a (spatially) correlated mixed model, for given correlation parameters
corrFamily constructors for random effect with AR(p) (autoregressive of order p) or ARMA(p,q) structure.
Extractors for information criteria such as AIC
Loa loa prevalence in North Cameroon, 1991-2001
Gryphon data
Fit mixed models with given correlation matrix
Cauchy correlation function and Cauchy formula term
Fitting generalized linear models without initial-value or divergence headaches
Interpolated Markov Random Field models
Multiple-Stage False Discovery Rate procedure
Control of matrix-algebraic methods
Pseudo R-squared
Example of yield stability analysis
S4 classes for structured matrices
corrFamily constructor for Interpolated Markov Random Field (IMRF) covariance structure approximating a 2D Matern correlation model.
Tests of fixed effects (LRTs and ANOVA tables).
Simulated data set for testing sparse-precision code
Matern correlation function and Matern formula term.
Internal functions for procedure using the ((I,0),(Z,X)) block-order
Fitting autoregressive models
Matern Correlation Structure as a corSpatial object
Assessing convergence for fitted models
Beta-response family object
Composite random effects
Genetic polymorphism in relation to migration in the blackcap
Conversion to input for procedures from lmerTest package
Arabidopsis genetic and climatic data
Control parameters of the HLfit fitting algorithm
Confidence intervals
corr_family
objects
Using a corrMatrix argument
Information about numerical problems
Designing new corrFamily descriptors for parametric correlation families
Specifying correlation structures
corrFamily definition
Fits a mixed model, typically a spatial GLMM.
Using corrFamily constructors and descriptors.
Random-effect structures for diallel experiments and other dyadic interactions
Interface for parallel computations
Interface for parallel computations
Utilities for regularization of a matrix
Functions to extract various components of a fit.
Likelihood ratio test of fixed effects.
Evaluating bootstrap replicates
Prediction from models with nearly-singular covariance matrices
Drop all possible single fixed-effect terms from a model
Fixing some parameters
Fitting multivariate responses
Fitting function for fixed- and mixed-effect models with GLM response.
Freight dataset
Extract information about how an object was obtained
Extract matrices from a fit
Estimation of prediction variance with bootstrap correction
Operations on lists of parameters
Extractors of arguments for functions from package RLRsim
Clear and trustworthy formulas and prior weights
Leverage extractor for HLfit objects
Initiate a fit from another fit
Controlling optimization strategy through initial values
Distribution families for Gamma and inverse Gamma-distributed random effects
Scaled distances between unique locations
Computation of “square root” of symmetric positive definite matrix
Virtual factor for multivariate responses
Link-linear regression models (LLMs)
Fitting methods (objective functions maximized)
Installing external libraries
Colorful plots of predictions in two-dimensional space.
Checking for (quasi-)separation in binomial-response model.
Analyzing multinomial data
Fit mixed-effects models incorporating pedigrees
Family function for negative binomial “2” response (including truncated variant).
Applying post-fit procedures on spaMM results
Information matrix
Fitting random effects in the residual dispersion model
spaMM options settings
Alternative negative-binomial family
Partial-dependence effects and plots
Model checking plots for mixed models
Family function for GLMs and mixed models with Poisson and zero-truncated Poisson response.
Lip cancer in Scotland 1975 - 1980
Structure of random effects
Declare corrFamily constructor for use in formula
Prediction and response variances
Extract model residuals
Prediction from a model fit
Residual variance extractor
Salamander mating data
Masks of seas or lands
Checking the rank of the fixed-effects design matrix
Internal spaMM Functions
spaMM conventions and differences from related fitting procedures
Reduce the size of fitted objects
A flashy color palette.
Level (Contour) Plots with better aspect ratio control (for geographical maps, at least)
S3 methods of generics defined in other packages
Simulate realizations of a fitted model.
Seed germination data
Inference in mixed models, in particular spatial GLMMs
Extract covariance or correlation components from a fitted model object
Updates a fit
Welding data set
Data from a resistivity experiment for semiconductor materials.
Parametric bootstrap
Selecting interfaces for parallelisation
Tracking progress of fits
Summary and print methods for fit and test results.