HI there
I am running this model in negative binomial regression, using glm.
I had no problems with running the model with a set of data, but now that
i'm trying to run if for new one. I always have this same error when
running the regression:
>
> #Run Regression
> x=cbind(factor2ind(d$year)
Hi,
Why sum() on a 10-item vector produces a different value than its
counterpart on a 2-item vector? I understand the problems related to
the arithmetic precision in storing decimal numbers in binary format,
but shouldn't the errors be equal regardless of the method used?
See my example:
> opti
Hi Allaisone,
If you want a data frame as the output you will have to put up with a
few NA values unless each Customer has the same number of diet types:
a1df<-read.table(text="CustomerIDDietType
1 a
1c
1b
2
Thank you all for your help and sorry for that.
On Sun, Feb 25, 2018 at 12:18 PM, Jeff Newmiller
wrote:
> Jim has been exceedingly patient (and may well continue to be so), but
> this smells like "failure to launch". At what point will you start showing
> your (failed) attempts at solving your o
It depends quite strongly on what you want to do with the result, but I wonder
if what is really needed might be a list of diettypes per person, i.e.
continuing from Eric's code
> On 25 Feb 2018, at 18:56 , Eric Berger wrote:
>
> Hi Allaisone,
> I took a slightly different approach but you mig
Jim has been exceedingly patient (and may well continue to be so), but this
smells like "failure to launch". At what point will you start showing your
(failed) attempts at solving your own problems so we can help you work on your
specific weaknesses and become self-sufficient?
--
Sent from my p
Hi Allaisone,
I took a slightly different approach but you might find this either as or
more useful than your approach, or at least a start on the path to a
solution you need.
df1 <-
data.frame(CustId=c(1,1,1,2,3,3,4,4,4),DietType=c("a","c","b","f","a","j","c","c","f"),
strin
I believe you need to spend time with an R tutorial or two: a data frame
(presumably the "table" data structure you describe) can *not* contain
"blanks" -- all columns must be the same length, which means NA's are
filled in as needed.
Also, 8e^5 * 7e^4 = 5.6e^10, which almost certainly will not fi
Hi Peter,
the "residuals()" function returns the residuals of a model fitted using
the "lm" function. For instances, using the example included in the help of
lm:
ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14)
trt <- c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69)
group <- gl(2
HI Jim and all,
I want to put one more condition. Include col2 and col3 if they are not
in col1.
Here is the data
mydat <- read.table(textConnection("Col1 Col2 col3
K2 X1 NA
Z1 K1 K2
Z2 NA NA
Z3 X1 NA
Z4 Y1 W1"),header = TRUE,stringsAsFactors=FALSE)
The desired out put would be
Col1 Col2 co
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