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hoa (version 2.1.4.1)

Higher Order Likelihood Inference

Description

Performs likelihood-based inference for a wide range of regression models. Provides higher-order approximations for inference based on extensions of saddlepoint type arguments as discussed in the book Applied Asymptotics: Case Studies in Small-Sample Statistics by Brazzale, Davison, and Reid (2007).

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Version

Install

install.packages('hoa')

Monthly Downloads

20

Version

2.1.4.1

License

GPL (>= 2) | file LICENCE

Homepage

https://www.r-project.org

Maintainer

Alex-Antoine Fortin

Last Published

February 16th, 2019

Functions in hoa (2.1.4.1)

Chlorsulfuron Data

contour.all.nlreg.profiles

Contour Method for `nlreg' Objects

Approximate Conditional Inference - Generic Function

Differentiate the Variance Function of a Nonlinear Model

Use coef() on a `nlreg' object

Use family() on a ``rsm'' object

Use family() on a ``cond'' object

Metsulfuron Methyl Data

Approximate Conditional Inference Object

Huber's Least Favourable Distribution

Maximum Adjusted Profile Likelihood Estimation --- Generic Function

`Daphnia Magna' Data

Use fitted() on a `nlreg' object

Approximate Conditional Inference for Logistic and Loglinear Models

Approximate Conditional Inference in Regression-Scale Models

Darwin's Data on Growth Rates of Plants

Returns the Observed Information Matrix --- Generic Function

family.rsm.object

Family Object for Regression-Scale Models

Compute the Log Likelihood for Nonlinear Heteroscedastic Models

Compute the Log Likelihood for Regression-Scale Models

Fraudulent Automobile Insurance Claims Data

Returns the Expected Information Matrix --- Generic Function

Higher Order Likelihood Inference

Fungal Infections Treatment Data

Helicopter Data

family.summary.cond

Use family() on a ``summary.cond'' object

House Price Data

Expected Information Matrix for `nlreg' Objects

make.family.rsm

Support for RSM Family Functions

Observed Information Matrix for `nlreg' Objects

Maximum Adjusted Profile Likelihood Estimates for a `nlreg' Object

Approximate Marginal Inference Object

nlreg.profile.objects

Profile Objects for Nonlinear Heteroscedastic Models

Use print() on a ``cond'' object

Nuclear Power Station Data

print.family.rsm

Use print() on a ``family.rsm'' object

Maximum Adjusted Profile Likelihood Object

print.nlreg.profiles

Use print() on a `nlreg.profile' and `all.nlreg.profiles' object

Use print() on a ``rsm'' object

Diagnostic Plots for Regression-Scale Models

Nonlinear Heteroscedastic Model Diagnostics

Nonlinear Heteroscedastic Model Object

Support for Functions rsm.fit and rsm.surv

Use print() on a ``marg'' object

Generate Plots for an Approximate Conditional Inference Object

Plot a fr Object

print.summary.nlreg.profiles

Use print() on a `summary.nlreg.profile' and `summary.all.nlreg.profiles' object

rsm.distributions

RSM Family Support Object

Extract All Parameters from a Model --- Generic Function

print.summary.rsm

Use print() on a ``summary.rsm'' object

Use print() on a `mpl' object

print.summary.mpl

Use print() on a `summary.mpl' object

Generate a RSM Family Object

Fit a Nonlinear Heteroscedastic Model via Maximum Likelihood

print.summary.nlreg

Use print() on a `summary.nlreg' object

Regression-Scale Model Object

Compute Residuals for Regression-Scale Models

nlreg.contours.object

Contour Object for Nonlinear Heteroscedastic Models

Use param() on a `nlreg' object

Radioimmunoassay Data

Fit a Regression-Scale Model Without Computing the Model Matrix

Generate Plots for an Approximate Marginal Inference Object

Fit a Regression-Scale Model

plot.nlreg.contours

Use plot() on a `nlreg.contours' object

plot.nlreg.diag

Diagnostic Plots for Nonlinear Heteroscedastic Models

var2cor.nlregmpl

Use var2cor() on a `nlreg' and `mpl' object

Calculate Variance-Covariance Matrix for a Fitted RSM Model

print.summary.cond

Use print() on a ``summary.cond'' object

plot.nlreg.profiles

Use plot() on a `profile.nlreg' and `all.profiles.nlreg' object

summary.nlreg.profile

Summary Method for Objects of Class `nlreg.profile'

Summary Method for Regression-Scale Models

Diagnostics for Regression-Scale Models

Use print() on a `nlreg' object

summary.all.nlreg.profiles

Summary Method for Objects of Class `all.nlreg.profiles'

print.nlreg.contours

Use print() on a `nlreg.contours' object

Summary Method for Objects of Class ``cond''

Convert Covariance Matrix to Correlation Matrix --- Generic Function

print.summary.marg

Use print() on a ``summary.marg'' object

Profile Method for `nlreg' Objects

residuals.nlreg

Use residuals() on a `nlreg' object

Support for `nlreg' package of `hoa' bundle

Fit a Regression-Scale Model Without Computing the Model Matrix

Fit an Empty Regression-Scale Model

Likelihood-Based Confidence Intervals Based on fr Object

Summary Method for Objects of Class ``marg''

Summary Method for `mpl' Objects

Summary Method for Nonlinear Heteroscedastic Models

Tangent exponential model: Higher Order Likelihood Approximation

Update and Re-fit a RSM Model Call

Use anova() on a ``rsmlist'' object

Crying Babies Data

AIDS Symptoms and AZT Use Data

ANOVA Table for a RSM Object

all.profiles.nlreg

Support for function `profile.nlreg'

Six Herbicide Data Sets

Differentiate the Mean Function of a Nonlinear Model