Description Usage Arguments Value Note Examples
Generates a data.frame
or data.table
with a
binary outcome, and a logistic model to describe it.
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b |
binomial predictors, the number of predictors which are binary, i.e. limited to 0 or 1 |
f |
factors, the number of predictors which are factors |
c |
continuous predictors, the number of predictors which are continuous |
n |
number of observations in the data frame |
nlf |
the no. of levels in a factor |
pb |
probability for binomnial predictors: the
probability of binomial predictors being =1 e.g. if
|
rc |
ratio for continuous variables the ratio
of levels of continuous variables to the total number of
observations n e.g. if |
py |
ratio for y the ratio of 1s to total
observations for the binomial predictors e.g. if
|
asFactor |
If |
model |
If |
timelim |
function will timeout after |
speedglm |
If |
If model=TRUE
: a list with the following values:
df or dt |
A |
model |
A model fit with
|
If
model=FALSE
a data.frame
or
data.table
as above.
genLogiDt
is faster and more efficient for larger
datasets.
Using asFactor=TRUE
with factors
which have a large number of levels (e.g. nlf >30
)
on large datasets (e.g. n >1000) can cause fitting
to be excessively slow.
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