Package 'meifly'

Calculcate coefficients for all models in ensemble. Returns raw, t-value, absolute t-value, and standardised coefficent values.

Description

Calculcate coefficients for all models in ensemble. Returns raw, t-value, absolute t-value, and standardised coefficent values.

Usage

## S3 method for class 'ensemble'
coef(object, ...)

Arguments

object	ensemble of models
...	other arguments ignored

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General ensemble of models from models in global workspace'

Description

General ensemble of models from models in global workspace'

Usage

findmodels(modeltype = "lm", dataset, pattern)

Arguments

modeltype	model class
dataset	if specified, all models must use this dataset
pattern	pattern of model object names to match

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Fit all combinations of x variables ($2^p$).

Description

This technique generalises fitbest. While it is much slower it will work for any type of model.

Usage

fitall(y, x, method = "lm", ...)

Arguments

y	vector y values
x	matrix of x values
method	name of method used to fit the model, e.g lm,rlm
...	other arguments passed on to method

Examples

y <- swiss$Fertility
x <- swiss[, -1]
mods <- fitall(y, x, "lm")

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Use the leaps package to generate the best subsets.

Description

Use the leaps package to generate the best subsets.

Usage

fitbest(formula, data, nbest = 10, ...)

Arguments

formula	model formula
data	data frame
nbest	number of subsets of each size to record
...	other arguments passed to regsubsets

Examples

y <- swiss$Fertility
mods <- fitbest(Fertility ~ ., swiss)

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Generate linear models by bootstrapping observations

Description

Generate linear models by bootstrapping observations

Usage

lmboot(formula, data, n = 100)

Arguments

formula	model formula
data	data set
n	number of bootstrapped data sets to generate

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Interactive model ensemble exploration.

Description

Interactive model ensemble exploration.

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Calculate residuals for all models in ensemble.

Description

Calculate residuals for all models in ensemble.

Usage

## S3 method for class 'ensemble'
residuals(object, ...)

Arguments

object	ensemble of models
...	other arguments ignored

Value

data.frame of class resid_ensemble

See Also

summary.resid_ensemble

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Returns degrees of freedom, log likelihood, R-squared, AIC, BIC and adjusted R-squared.

Description

Returns degrees of freedom, log likelihood, R-squared, AIC, BIC and adjusted R-squared.

Usage

## S3 method for class 'ensemble'
summary(object, ...)

Arguments

object	ensemble of models
...	other arguments ignored

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Summarise residuals from ensemble.

Description

Summarise residuals from ensemble.

Usage

## S3 method for class 'resid_ensemble'
summary(object, data = attr(object, "data"), ...)

Arguments

object	model residuals from residuals.ensemble
data	associated data set
...	other arguments ignored

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Summarise variable ensemble.

Description

Provides variable level statistics.

Usage

## S3 method for class 'variable_ensemble'
summary(object, ...)

Arguments

object	ensemble of models
...	other arguments ignored

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