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hoa (version 2.1.1)

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

36

Version

2.1.1

License

GPL (>= 2) | file LICENCE

Homepage

http://www.r-project.org

Maintainer

Alex-Antoine Fortin

Last Published

July 4th, 2015

Functions in hoa (2.1.1)

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

family.rsm.object

Family Object for Regression-Scale Models

Helicopter Data

Higher Order Likelihood Inference

Maximum Adjusted Profile Likelihood Estimates for a `nlreg' Object

nlreg.contours.object

Contour Object for Nonlinear Heteroscedastic Models

Nonlinear Heteroscedastic Model Diagnostics

Plot a fr Object

Huber's Least Favourable Distribution

ANOVA Table for a RSM Object

Chlorsulfuron Data

`Daphnia Magna' Data

Generate a RSM Family Object

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

plot.nlreg.profiles

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

Diagnostic Plots for Regression-Scale Models

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

print.summary.nlreg

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

Calculate Variance-Covariance Matrix for a Fitted RSM Model

Metsulfuron Methyl Data

Maximum Adjusted Profile Likelihood Object

Generate Plots for an Approximate Conditional Inference Object

Generate Plots for an Approximate Marginal Inference Object

Support for `nlreg' package of `hoa' bundle

Summary Method for `mpl' Objects

Summary Method for Regression-Scale Models

Fit a Regression-Scale Model Without Computing the Model Matrix

Summary Method for Objects of Class ``marg''

Returns the Expected Information Matrix --- Generic Function

var2cor.nlregmpl

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

Summary Method for Nonlinear Heteroscedastic Models

Support for Functions rsm.fit and rsm.surv

Returns the Observed Information Matrix --- Generic Function

print.nlreg.contours

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

print.family.rsm

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

Differentiate the Mean Function of a Nonlinear Model

Radioimmunoassay Data

Tangent exponential model: Higher Order Likelihood Approximation

Likelihood-Based Confidence Intervals Based on fr Object

all.profiles.nlreg

Support for function `profile.nlreg'

Crying Babies Data

contour.all.nlreg.profiles

Contour Method for `nlreg' Objects

Use fitted() on a `nlreg' object

print.summary.marg

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

Fit a Regression-Scale Model Without Computing the Model Matrix

Profile Method for `nlreg' Objects

Fit a Regression-Scale Model

Approximate Conditional Inference - Generic Function

Expected Information Matrix for `nlreg' Objects

House Price Data

Observed Information Matrix for `nlreg' Objects

Maximum Adjusted Profile Likelihood Estimation --- Generic Function

Use print() on a `mpl' object

print.summary.cond

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

print.summary.mpl

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

residuals.nlreg

Use residuals() on a `nlreg' object

Compute Residuals for Regression-Scale Models

Differentiate the Variance Function of a Nonlinear Model

Six Herbicide Data Sets

Approximate Conditional Inference Object

Darwin's Data on Growth Rates of Plants

Approximate Conditional Inference in Regression-Scale Models

AIDS Symptoms and AZT Use Data

Use print() on a `nlreg' object

Nonlinear Heteroscedastic Model Object

family.summary.cond

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

Approximate Conditional Inference for Logistic and Loglinear Models

Approximate Marginal Inference Object

Fit a Nonlinear Heteroscedastic Model via Maximum Likelihood

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

Fit an Empty Regression-Scale Model

Convert Covariance Matrix to Correlation Matrix --- Generic Function

Update and Re-fit a RSM Model Call

Use coef() on a `nlreg' object

Fungal Infections Treatment Data

plot.nlreg.contours

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

Compute the Log Likelihood for Nonlinear Heteroscedastic Models

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

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

print.nlreg.profiles

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

Diagnostics for Regression-Scale Models

print.summary.rsm

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

Use param() on a `nlreg' object

plot.nlreg.diag

Diagnostic Plots for Nonlinear Heteroscedastic Models

rsm.distributions

RSM Family Support Object

Fraudulent Automobile Insurance Claims Data

Compute the Log Likelihood for Regression-Scale Models

Summary Method for Objects of Class ``cond''

summary.all.nlreg.profiles

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

Regression-Scale Model Object

Extract All Parameters from a Model --- Generic Function

make.family.rsm

Support for RSM Family Functions

Nuclear Power Station Data

nlreg.profile.objects

Profile Objects for Nonlinear Heteroscedastic Models

print.summary.nlreg.profiles

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

summary.nlreg.profile

Summary Method for Objects of Class `nlreg.profile'