ds.anova: Fit an Analysis of Variance Model

In paularaissa/distStatsClient: Distributed Multiple Imputations

Description

Computes the combined equations for analysis of variance.

Usage

ds.anova(formula = NULL, model, weights = NULL, learningrate = 0.01,
  dif = 1e-09, checks = FALSE, datasources = NULL)

Arguments

formula	a character that can be coerced to an object of class formula. It is a symbolic description of the model to be fitted.
model	a character, the name of regression model. If model is set to 'linear', computes Anova for a linear model; if model is set to 'logistic', computes Anova for a logistic model; if model is set to 'poissin', computes Anova for a Poisson model.
weights	a character, the name of an optional vector of weights to be used in the fitting process. Should be null or a numeric vector.
learningrate	a numeric, controls how much we are adjusting the regression model. It is an optional parameter. Should be set if the Anova will be computed for logistic ou Poisson model.
dif	a numeric, controls the learning convergence. It is an optional parameter. Should be set if the Anova will be computed for logistic ou Poisson model.
checks	a boolean, if TRUE (default) checks that verify elements on the server side such checks lengthen the run-time so the default is FALSE and one can switch these checks on (set to TRUE) when faced with some error(s).
datasources	a list of opal object(s) obtained after login in to opal servers; these objects hold also the data assign to R, as data frame, from opal datasources.

Details

The variation between and within groups for a one-way analysis of variance generalizes to model variation and residual variation which partition the total variation SSD[model] = ∑[i](y[i]-y*)^2. This can be applied only when the model contains an intercept. The model is considered to be statistically significant if it can account for a large amount of variability in the response.

Value

Returns the Anova table with the following components:

Df	degrees of freedon
Sum.Sq	sum of squares
Mean.Sq	mean of squares
F.value	f-test
Pr(>F)	p-value from f-statistic

Dependencies

getAnova

Author(s)

Paula Raissa Costa e Silva

paularaissa/distStatsClient documentation built on June 19, 2019, 12:43 a.m.