Last data update: 2014.03.03

R: Hierarchical Regression Model Generation
create_model_objectsR Documentation

Hierarchical Regression Model Generation

Description

Hierarchical Regression Model Generation

Usage

create_model_objects(formulas, dataset, type = "gaussian")

Arguments

formulas

A set of lm formulas, created with create_formula_objects

dataset

A data frame containing variables refered to in formulas, passed to data argument of lm

type

Family argument to pass to glm. Specify "binomial" for binary logistic regression models.

Value

A list of lm model objects

Examples

create_model_objects(create_formula_objects("y", c("lag.quarterly.revenue")
, c("price.index")), dataset = freeny)
freeny_model_formulas <- create_formula_objects("y", c("lag.quarterly.revenue")
, c("price.index"))
create_model_objects(freeny_model_formulas, dataset = freeny)

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(AutoModel)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/AutoModel/create_model_objects.Rd_%03d_medium.png", width=480, height=480)
> ### Name: create_model_objects
> ### Title: Hierarchical Regression Model Generation
> ### Aliases: create_model_objects
> 
> ### ** Examples
> 
> create_model_objects(create_formula_objects("y", c("lag.quarterly.revenue")
+ , c("price.index")), dataset = freeny)
> freeny_model_formulas <- create_formula_objects("y", c("lag.quarterly.revenue")
+ , c("price.index"))
> create_model_objects(freeny_model_formulas, dataset = freeny)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>