Description Usage Arguments Details Value See Also Examples
Fit a PIM
1 2 3 4 5 6 7 8 9 10 11 12 | pim(formula, data, link = c("logit", "identity", "probit", "inverse",
"1/mu^2", "log"), blocking.variables = character(), poset = noselfposet,
leftsuffix = "_L", rightsuffix = "_R", interpretation = c("difference",
"regular", "marginal", "symmetric"), na.action = na.fail,
estimator = estimator.nleqslv(),
varianceestimator = varianceestimator.sandwich(), lhs = c("PO", "<",
"<="), keep.data = FALSE, verbosity = 0, nicenames = TRUE,
interactions.difference = (interpretation != "marginal"),
extra.nicenames = data.frame(org = character(), nice = character(),
stringsAsFactors = FALSE), check.symmetric = (interpretation == "regular"),
threshold = 1e-06, weights = NULL,
pseudoweights = pseudoweights.default)
|
formula |
Original formula |
data |
Context where the formula |
link |
Name of the link function (defaults to |
blocking.variables |
Character vector holding column names that hold blocking variables. |
poset |
Matrix of two columns indicating what the original observation number is
for the left and right real observation in the pseudo-observation. Alternatively, can
be a function like |
leftsuffix, rightsuffix |
Suffixes that will be added to the 'left' and 'right' observation's column name in the pseudo-observation. Note: no checking is done that these suffixes are safe, so the wrong suffixes may lead to unexpected behaviour. |
interpretation |
If |
na.action |
Defaults to |
estimator |
Function like the result of |
varianceestimator |
Function like the result of |
lhs |
|
keep.data |
If |
verbosity |
The higher this value, the more levels of progress and debug information is displayed (note: in R for Windows, turn off buffered output) |
nicenames |
Defaults to |
interactions.difference |
If |
extra.nicenames |
Should be a |
check.symmetric |
Defaults to |
threshold |
When checking the symmetry condition, how much digression is allowed. |
weights |
Defaults to |
pseudoweights |
Defaults to |
Some of the items in the return value may be missing if parts of the estimation
fail. See pim.fit
for this.
If estimator
was estimator.glmnet
, The return value gets as an additional class
"glmnetpim"
.
For more details on how to use this function and its parameters, we refer the reader to
vignette("pim")
.
An object of class pim
,which is a list with items:
coefficients |
Parameter estimates. See |
morefitinfo |
Parameter estimation info. See |
vcov |
Covariance estimates. See |
morevarfitinfo |
Covariance estimation info. See |
varestimationerror |
Only present if covariance estimation failed. See |
call |
Call used when running this function. |
formula |
Passed in formula. |
link |
Name of the link function (defaults to |
fitted.values |
Predicted pseudo-observation values. |
pfd |
Object of class |
data |
Passed in |
estimator.nleqslv
varianceestimator.sandwich
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | set.seed(1)
iris$out<-factor(sample(2, nrow(iris), replace=TRUE))
iris$xord<-as.ordered(iris$Species)
pima<-pim(out~Sepal.Length, data=iris, link="logit", interpretation="regular")
pimb<-pim(out~I((R(Sepal.Length) - L(Sepal.Length))/sqrt(R(Sepal.Length) * L(Sepal.Length)) ), data=iris,
link="logit", interpretation="regular", extra.nicenames=data.frame(
org="I((R(Sepal.Length) - L(Sepal.Length))/sqrt(R(Sepal.Length) * L(Sepal.Length)) )",
nice="Sepal.Length.WDiff", stringsAsFactors=FALSE))
pimc<-pim(out~O(xord), data=iris, link="logit", interpretation="regular")
##And an example with weighted fitting
iris50<-iris[sample.int(nrow(iris), 50),]
rwt50<-runif(50) #50 random weights
pimd<-pim(out~O(xord), data=iris50, link="logit", interpretation="regular",
weights = rwt50)
|
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