NeEDS4BigData (version 1.0.1)

GenModelMissGLMdata: Generate data for Generalised Linear Models under model misspecification scenario

Description

Function to simulate big data under Generalised Linear Models for the model misspecification scenario through any misspecification type.

Usage

GenModelMissGLMdata(N,X_Data,Misspecification,Beta,Var_Epsilon,family)

Value

The output of GenModelMissGLMdata gives a list of

Complete_Data a matrix for Y,X and f(x)

Arguments

N

the big data size

X_Data

a matrix for the covariate data

Misspecification

a vector of values for the misspecification

Beta

a vector for the model parameters, including the intercept and misspecification term

Var_Epsilon

variance value for the residuals

family

a character vector for "linear", "logistic" and "poisson" regression from Generalised Linear Models

Details

Big data for the Generalised Linear Models are generated by the "linear", "logistic" and "poisson" regression types under model misspecification.

References

adewale2009robustNeEDS4BigData

adewale2010robustNeEDS4BigData

Examples

Beta<-c(-1,0.75,0.75,1); Var_Epsilon<-0.5; family <- "linear"; N<-10000
X_1 <- replicate(2,stats::runif(n=N,min = -1,max = 1))

Temp<-Rfast::rowprods(X_1)
Misspecification <- (Temp-mean(Temp))/sqrt(mean(Temp^2)-mean(Temp)^2)
X_Data <- cbind(X0=1,X_1);

Results<-GenModelMissGLMdata(N,X_Data,Misspecification,Beta,Var_Epsilon,family)

Results<-GenModelMissGLMdata(N,X_Data,Misspecification,Beta,Var_Epsilon=NULL,family="logistic")

Results<-GenModelMissGLMdata(N,X_Data,Misspecification,Beta,Var_Epsilon=NULL,family="poisson")