Description Usage Arguments Details Value Dependencies Author(s)
Computes the combined equations for analysis of variance.
1 2 |
formula |
a character that can be coerced to an object of class |
model |
a character, the name of regression model.
If |
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 |
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.
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 |
getAnova
Paula Raissa Costa e Silva
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