Displaying 4 results from an estimated 4 matches for "pformula".
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2003 Dec 19
1
problem with rm.impute of the Design library
...70, 6030, NA, 6880,
5330, 5700, NA, 6220, 5240, 5850, 5960, 4910, 5550),
y4<-c(7640, 6840, 6900, 6010, 7780, 7650, 7610, 7000, NA, NA, 7720,
5990, 6340, NA, 7360, 5910, 6310, NA, 5350, 5880)),
last=c(4, 4, 4, 4, 4, 4, 4, 4, 3, 2, 4, 4, 4, 1, 4, 4, 4, 3, 4, 4))
imp.df <- rm.impute(pformula = ~ pre+pro+sex, y = df$y, last = df$last,
rformula = ~ pre+pro+sex, n.impute = 2, data = df)
Here the error:
> imp.df <- rm.impute(pformula = ~ pre+pro+sex, y = df$y, last = df$last,
+ rformula = ~ pre+pro+sex, n.impute = 2, data = df)
Imputation 1
Time period 1 : no dropouts
Error in...
2009 Nov 09
3
Bug in all.equal() or in the plm package
...will be used
> all.equal(zz$formula,zz$formula)
[1] TRUE
Warning message:
In if (length(target) != length(current)) return(paste("target,
current differ in having response: ", :
the condition has length > 1 and only the first element will be used
> class(zz$formula)
[1] "pFormula" "Formula" "formula"
======================================
The last commands show that the warning message comes from comparing
the elements "formula", which are of the class "pFormula" (inheriting
from "Formula" and "formula"). It...
2013 May 17
2
How could I see the source code of functions in an R package?
...)
}
if (inherits(data, "pdata.frame") && !is.null(index))
warning("the index argument is ignored because data is a
pdata.frame")
if (!inherits(data, "pdata.frame"))
data <- pdata.frame(data, index)
if (!inherits(formula, "pFormula"))
formula <- pFormula(formula)
if (length(formula)[2] == 2)
formula <- expand.formula(formula)
cl <- match.call()
mf <- match.call(expand.dots = FALSE)
m <- match(c("formula", "data", "subset", "na.action")...
2013 Sep 04
2
Attribute Length Error when Trying plm Regression
...ames' attribute [996] must be the same length as the vector [0]
I know the data recognizes that I have 5 columns. I also know that there's
nothing wrong with row 996 (I even want back and checked for hidden
characters in the original .csv file).
traceback() was useless:
4: pmodel.response.pFormula(formula, data, model = model, effect = effect,
theta = theta)
3: pmodel.response(formula, data, model = model, effect = effect,
theta = theta)
2: plm.fit(formula, data, model, effect, random.method, inst.method)
1: plm(h ~ o + m + a, data = drugsXX, index = c("h",...