> On Apr 15, 2016, at 5:58 PM, Paul Tremblay wrote:
>
> I have the following (simplified) vectors:
> index <- c("shoe" "shirt" "fruit")
> cost <- c(100, 50, 2)
> data <- c("shirt", "shoe", "vegetable")
>
> I want my outcome to be:
>
> (50, 100, 0)
>
> (shirt => 50, shoe => 100, vegetable =>
Thanks bill that will give the result I would like, however the example I
used is not the actual data I'm working with. I have 25 or so columns,
each with 1-5 factors and 4 off them are numerical.
On Fri, Apr 15, 2016 at 5:44 PM, William Dunlap wrote:
> Since you only have 3 predictors, each ca
hi, i am new in this field.
I am now writing a code in robustness simulation study. I have written a brief
code "for loop" for the factor (samples sizes d,std deviation ) , i wish to
test them in gamma distribution with equal and unequal skewness, with the above
for loop in a single code if pos
Why? RODBC is usable for reading data, but not particularly well adapted for
inserting data. So if you have a solution, why are you still looking for one?
--
Sent from my phone. Please excuse my brevity.
On April 15, 2016 2:47:52 PM PDT, Divakar Reddy
wrote:
>Hi,
>
>I have requirement to mov
I have the following (simplified) vectors:
index <- c("shoe" "shirt" "fruit")
cost <- c(100, 50, 2)
data <- c("shirt", "shoe", "vegetable")
I want my outcome to be:
(50, 100, 0)
(shirt => 50, shoe => 100, vegetable => not found, so 0)
I have written the following function:
for (i in custom_l
Since you only have 3 predictors, each categorical with a small number of
categories, you can use expand.grid to make a data.frame containing all
possible combinations and give that the predict method for your model to
get all possible predictions.
Something like the following untested code.
n
I need the output to have groups and the probability any given record in
that group then has of being in the response class. Just like my email in
the beginning i need the output that looks like if A and if B and if C then
%77 it will be D. The examples you provided are just simply not similar.
Th
Hi,
I have requirement to move the data from Linux local path( ex
/home/user/sample.txt) to hadoop HDFS using RODBC in R
I knew that we can move the data using rhive comamnds like *rhive.put*
and *rhive.get
*but looking for similar commands using RODBC as well.
I would appreciate for your input
> On Apr 15, 2016, at 1:07 PM, deva d wrote:
>
> Hi
>
> I need a bit of guidance on tests and methods to look for multicollinearity
> and Endogeniety while using plspm
R help is not set up for statistical guidance. You probably need to post a more
detailed question about your data and analyti
Many basic summary stats in R will not work (i.e. usually return an NA) if
there are NAs in the data unless you explicitylauthorize it to do so.
With your data set df
with(df, mean(Dat2, na.rm = TRUE))
[1] 5
This by the way is functionally the same as
mean(df$Dat2, na.rm = TRUE)
It's just easi
Hi
I need a bit of guidance on tests and methods to look for multicollinearity
and Endogeniety while using plspm
Pl help
--
T&R
...
Deva
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list -- To UNSUBSCRI
Please don't post in HTML. Your post is almost unreadable
Also,lease have a look at
http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example
and/or http://adv-r.had.co.nz/Reproducibility.html for some suggestions about
what you should include in your question.
Welco
There are a number of articles and even books at the R site that are worth
looking at. Look Dnder documentation on the main page of the site.
This link may also help http://www.burns-stat.com/documents/tutorials/
John Kane
Kingston ON Canada
> -Original Message-
> From: kipkorirfrank
> On Apr 15, 2016, at 6:07 AM, PIKAL Petr wrote:
>
> Hi
>
> Keep your answers to R help (others can help you too)
>
> From the warning message it seems to me possible that function ReadExi needs
> to write something to the working directory. As I said I am not an expert in
> this package, bu
Hi,
I am trying to do an LRSM Rasch analysis for 72-item data. 67 of the
items are binary, and 5 are ternary. I have tried it with and without a
specified matrix, and cannot get it to work.
The primary problems I am having are:
1. Without a matrix, I get an error:
Error in `rownames<-`(`*tmp*`
Yeah, this is a bit lengthy, but it's a vexing problem.
First, I'm working on learning R, mainly by using it and coming more
from a programming aspect (I have the books and have gone through them,
but learn best by doing). I have multiple projects going where R is
almost necessary. I learned
Quit trying to eliminate heteroscedasticity in your data - there is
information there in the pattern of changing variances. I would suggest
instead that you go directly after modeling the change in entire
distributional form by using quantile regression (package quantreg). So,
for example, depen
Hello,
I'm cc'ing R-Help.
Sorry but your question was asked 3.5 years ago, I really don't
remember it. Can you please post a question to R-Help, with a
reproducible example that describes your problem?
Rui Barradas
Citando catalin roibu :
> Dear Rui,
>
> I helped me some time ago with
> Therneau, Terry M , Ph D
> on Fri, 15 Apr 2016 06:58:22 -0500 writes:
> I'd like to get interaction terms in a model to be in
> another form. Namely, suppose I had variables age and
> group, the latter a factor with levels A, B, C, with age *
> group in the model.
I was right that there is an easy answer!
Thanks for the 3 quick answers, all three correct and useful.
Terry Therneau
On 04/15/2016 07:15 AM, Thierry Onkelinx wrote:
Dear Terry,
Does fitting group + age:group instead of age*group solves your problem?
Best regards,
ir. Thierry Onkelinx
2
Hi
Keep your answers to R help (others can help you too)
From the warning message it seems to me possible that function ReadExi needs to
write something to the working directory. As I said I am not an expert in this
package, but commands from help
R> make.gal.env(galname='galenv', gal.path='Ex
Try using
~ group/age
or even
~ 0 + group/age
Both have all three group-specific slopes but differ with respect to the
intercept codings. The latter has three group-specific intercepts as well.
But the former has an intercept corresponding to the reference group A and
then the usual treatm
Hi
If you recently start with R maybe you shall spend some time with R intro
document to understand R basics.
I looked to ExiMiR package and I must say that although I am after 20 years
quite familiar with R I have problems to understand what I should do and I
would need to study thoroughly ho
Dear Terry,
Does fitting group + age:group instead of age*group solves your problem?
Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 An
On 15/04/2016 4:16 AM, Akhilesh Singh wrote:
Dear All,
Thanks for your help. However, I would like to draw your attention to the
following:
Actually, I was replicating the Example 2.3, using the dataset
"brainsize.txt" given in Section 2.3.3 ("Summarize by group") at page 55,
of a famous book "
Hello Sir/ma'am,
Greetings for the Day !
I am Jyoti Sharma, from India and recently start working on R. I am new in
this field and my knowledge is not up to the mark, so if I sound dumb then
please forgive me.
I tried to read some text file in R so that I can do further analysis on
those files.
Books don't rewrite themselves retroactively
NEWS for 3.0.0 has
• mean() for data frames and sd() for data frames and matrices are
defunct.
and 3.0.0 was released April 3, 2013.
A book published in 2012 would likely be based on R 2.13.x or maybe even 2.12.x.
So mean(dataframe) wor
I'd like to get interaction terms in a model to be in another form. Namely, suppose I had
variables age and group, the latter a factor with levels A, B, C, with age * group in the
model. What I would like are the variables "age:group=A", "age:group=B" and
"age:group=C" (and group itself of c
The 6th annual Modern Modeling Methods Conference will be held on May 24-25,
2016 at the University of Connecticut. This year's keynote speakers are Andrew
Gelman and Bengt Muthen. May 23rd, Bengt Muthen is offering a full-day
pre-conference workshop on Advances in Latent Variable Modeling in M
Hi Elahe,
When you want to include a usable toy data frame, it's better to use
something like:
dput(mydata[1:100])
So if we have a data frame like this:
mydata<-data.frame(RE=sample(5:50,100,TRUE),
LU=sample(1500:4500,100),
COUNTRY=factor(sample(c("DE","FR","JP","AU"),100,TRUE)),
Light=fac
> On Apr 15, 2016, at 1:16 AM, Akhilesh Singh
> wrote:
>
> Dear All,
>
> Thanks for your help. However, I would like to draw your attention to the
> following:
>
> Actually, I was replicating the Example 2.3, using the dataset
> "brainsize.txt" given in Section 2.3.3 ("Summarize by group") at
Hi,
I am currently trying to do a GLMM on a dataset with percent cover of
seagrass (dep. var) and a suite of explanatory variables including algal
(AC) and epiphyte cover (EC), rainfall, temperature and sunshine hours.
M2=glmer(SG~AC+EC+TP+SS+RF+(1|Location/fSi/fTr),
family=binomial,data=data,n
Dear All,
Thanks for your help. However, I would like to draw your attention to the
following:
Actually, I was replicating the Example 2.3, using the dataset
"brainsize.txt" given in Section 2.3.3 ("Summarize by group") at page 55,
of a famous book "R by Example" written by "Jim Albert and Maria
33 matches
Mail list logo
