R Graphical Manual

Last data update: 2014.03.03

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R Release (3.2.3)
CranContrib
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Results 1 - 10 of 31 found.
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wald.test (Package: aod) : Wald Test for Model Coefficients

Computes a Wald chi-squared test for 1 or more coefficients, given their variance-covariance matrix.

● Data Source: CranContrib
● Keywords: htest
● Alias: print.wald.test, wald.test
● 0 images

vcov-methods (Package: aod) : Methods for Function "vcov" in Package "aod"

Extract the approximate var-cov matrix of estimated coefficients from fitted models.

● Data Source: CranContrib
● Keywords: methods
● Alias: geeglm-class, geese-class, vcov,geeglm-method, vcov,geese-method, vcov,glimML-method, vcov,glimQL-method
● 0 images

varbin (Package: aod) : Mean, Variance and Confidence Interval of a Proportion

This function computes the mean and variance of a proportion from clustered binomial data (n, y), using various methods. Confidence intervals are computed using a normal approximation, which might be inappropriate when the proportion is close to 0 or 1.

● Data Source: CranContrib
● Keywords: htest
● Alias: show,varbin-class, varbin
● 0 images

varbin-class (Package: aod) : Representation of Objects of Formal Class "varbin"

Representation of the output of function varbin used to estimate proportions and their variance under various distribution assumptions.

● Data Source: CranContrib
● Keywords: classes
● Alias: show,varbin-method, varbin-class
● 0 images

summary.glimML-class (Package: aod) : Summary of Objects of Class "summary.glimML"

Summary of a model of formal class “glimML” fitted by betabin or negbin.

● Data Source: CranContrib
● Keywords: classes
● Alias: show,glimML-class, show,summary.glimML-method, summary,glimML-method, summary.glimML-class
● 0 images

summary,aic-method (Package: aod) : Akaike Information Statistics

Computes Akaike difference and Akaike weights from an object of formal class “aic”.

● Data Source: CranContrib
● Keywords: methods
● Alias: show,aic-method, summary,aic-method
● 0 images

splitbin (Package: aod) : Split Grouped Data Into Individual Data

The function splits grouped data and optional covariates into individual data. Two types of grouped data are managed by splitbin:

● Data Source: CranContrib
● Keywords: datagen
● Alias: splitbin
● 0 images

residuals-methods (Package: aod) : Residuals for Maximum-Likelihood and Quasi-Likelihood Models

Residuals of models fitted with functions betabin and negbin (formal class “glimML”), or quasibin and quasipois (formal class “glimQL”).

● Data Source: CranContrib
● Keywords: regression
● Alias: residuals,glimML-method, residuals,glimQL-method
● 0 images

raoscott (Package: aod) : Test of Proportion Homogeneity using Rao and Scott's Adjustment

Tests the homogeneity of proportions between I groups (H0: p_1 = p_2 = ... = p_I ) from clustered binomial data (n, y) using the adjusted chi-squared statistic proposed by Rao and Scott (1993).

● Data Source: CranContrib
● Keywords: htest
● Alias: raoscott, show,raoscott-class
● 0 images

quasipois (Package: aod) : Quasi-Likelihood Model for Counts

The function fits the log linear model (“Procedure II”) proposed by Breslow (1984) accounting for overdispersion in counts y.

● Data Source: CranContrib
● Keywords: regression
● Alias: quasipois
● 0 images