Description Usage Arguments Details Value See Also Examples
Get a set of pseudo-observation observation indices
1 2 3 4 5 6 7 8 9 10 11 12 | fullposet(data, formula, weights = NULL, verbosity = 0)
noselfposet(data, formula, weights = NULL, verbosity = 0)
lexiposet(data, formula, weights = NULL, verbosity = 0)
onewayposet(data, formula, weights = NULL, verbosity = 0)
forcedcolorderonewayposet(columnnames = NULL)
forcedposet(diffcols = NULL, LLessRcols = NULL, RLessLcols = NULL,
no.equals = TRUE)
|
data |
Context where the formula |
formula |
Original formula |
weights |
Vector of weights per row of |
verbosity |
The higher this value, the more levels of progress and debug information is displayed (note: in R for Windows, turn off buffered output) |
columnnames |
column names that will be used to imply order. |
diffcols |
column names that will be used to imply order. |
LLessRcols |
column names where you want the left observation to be smaller. |
RLessLcols |
column names where you want the right observation to be smaller |
no.equals |
if |
The provided implementations differ as follows:
fullposet
Contains all combinations of rowindices.
noselfposet
The same as fullposet, but excluding the rowcombinations
with identical indexes.
lexiposet
Check that predicting variables can be ordered, and select
only combinations where the predictors are bigger on the right side.
onewayposet
Similar to lexiposet
, but simply uses row index.
forcedcolorderonewayposet
First reorders the data based on a set of given
column names. Note: the other functions here are to be passed along as
poset=fullposet
, this one needs poset=forcedcolorderonewayposet(c("col1", "col2"))
forcedposet
Starts from all observations, but excludes the ones where
the combinations of the columns in diffcols
are the same in left and right observation
the combinations of the columns in LLessRcols
in the left observation
are greater than the one in the right observation (equals are dropped too if no.equals=TRUE
)
the combinations of the columns in RLessLcols
in the right observation
are greater than the one in the left observation (equals are dropped too if no.equals=TRUE
)
As a side effect, the data is also sorted wrt the LLessRcols
(ascending) and then according to
the RLessLcols
(descending).
oldpimposet
and oldpimposetbft
Sorts the data according to all
predictors, then does oneway-style. These are mainly provided for comparison to a
previous implementations of pim.
List with 3 items:
data |
Similar to the passed along |
poset |
Matrix of two columns indicating what the original observation number is for the left and right real observation in the pseudo-observation. |
weights |
Weight to be applied to each row of the dataset. Should contain one
weight per row of data (and match its order) or equal |
1 2 3 4 5 |
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