Hi,
No problem,
You could try:
library(tseries)
res6 <- do.call(rbind,lapply(lst1[sapply(lst1,function(x)
!(all(rowSums(is.na(x))>0)))],function(x) {resid <-
residuals(lm(rate~.,data=x)); unlist(jarque.bera.test(resid)[1:3])}) )
A.K.
On Wednesday, November 27, 2013 7:47 PM, Tomasz Schabek
<schabek.tom...@gmail.com> wrote:
Great!
Thank you for help one more time!
yes, you are right - jarque.bera.test() should be applied to a vector, so the
deal is: residuals from each of those 123 regressions captured by e.g:
"resid <-residuals(model)" and "jarque.bera.test(resid)" are tested in
jarque.bera.test(). Could you manage it?
You are really helpful and kind person!
Kind regards,
Atenciosamente,
Pozdrawiam,
T. S.
On 28 November 2013 01:33, arun <smartpink...@yahoo.com> wrote:
>
>Hi,
>In that case:
>
> lst5 <- lapply(lst1[sapply(lst1,function(x)
>!(all(rowSums(is.na(x))>0)))],function(x) vif(lm(rate~., x)))
>res5 <- do.call(rbind,lst5)
>
>
>As I mentioned earlier, it is not clear how you wanted to test
>jarque.bera.test(). Also, the results from lst3,lst4,lst5 etc could be saved
>using capture.output() (not tested though). Or if you wanted to modify it and
>wanted only specific categories, for example:
> res4 <- do.call(rbind,lapply(lst4,function(x) unlist(x[-4])))
>
>
>
>
>
>On Wednesday, November 27, 2013 7:21 PM, nooldor <nool...@gmail.com> wrote:
>
>Thank you for fast answer!
>
>and big THANK for help!
>
>I found error in the previous script (it was doing 334 regressions on 123
>length vectors and it should be opposite: 123 regressions on 334 length
>vector) anyway I modify it:
>
>data<-read.table("reg3-dane.csv", head=T, sep=";", dec=",")
>>data$indx <- as.numeric(gl(123*334,334,123*334))
>>lst1 <- split(data[,-16],data[,16])
>>any(sapply(lst1,nrow)!=123)
>>#[1] FALSE
>>lapply(lst1[sapply(lst1,function(x) !(all(rowSums(is.na(x))>0)))],function(x)
>>summary(lm(rate~cap.log,data=x)) )
>>capture.output(lst2,file="nooldor.txt")
>>it's ok now (at least when I compared regression summary from excel and R it
>>was the same :-) )
>
>
>capture.output(lst2,file="nooldor.txt") works fine!
>
>packages:
>vif {car}
>jarque.bera.test {tseries}
>
>ncvTest {car}
>durbinWatsonTest {car}
>
>
>R version 3.0.2 (2013-09-25)
>
>
>T.S.
>
>
>On 28 November 2013 00:38, arun <smartpink...@yahoo.com> wrote:
>
>Hi,
>>
>>2. You need to tell which package you are using.
>>
>>3. Does this work for you?
>>capture.output(lst2,file="nooldor.txt")
>>
>>4.
>>
>>
>>
>>lst2
>> <- lapply(lst1[sapply(lst1,function(x)
>>!(all(rowSums(is.na(x))>0)))],function(x)
>>print(summary(lm(rate~.,data=x))) ###prints the output on R console
>>
>>A.K.
>>
>>
>>
>>Hi,
>>
>>Thank you for patience and help :-)
>>
>>now the code looks like that:
>>
>>
>>data<-read.table("reg3-dane.csv", head=T, sep=";", dec=",")
>>>data$indx <- as.numeric(gl(334*123,123,334*123))
>>>lst1
>>
>> <- split(data[,-16],data[,16]) # 1. by changing "16" parameter I can
>> add or remove variables (also by modyfing the "reg3-dane.csv" file),
>>right?
>>>any(sapply(lst1,nrow)!=123)
>>>#[1] FALSE
>>
>>>lst2 <- lapply(lst1[sapply(lst1,function(x)
>>>!(all(rowSums(is.na(x))>0)))],function(x)
>>>summary(lm(rate~cap.log+liqamih.log+pbv,data=x)) )
>>>length(lst2)
>> # 2.where I can place the test for each (from 123) regression like
>>jarque.bera.test()
>>vif()
>>ncvTest()
>>durbinWatsonTest() to have it saved with regression summary? and 3. how
>>to get those list with results more user-friendly? I would like to get
>>the report
>>>#[1] 334
>>>
>>
>>is it ok?
>>
>>Could you help me with the questions in remarks above?
>>
>>And could you modify the script to also print the summary (and tests) of each
>>regression (each of 123) in console?
>>
>>
>>Best wishes!
>>T.S.
>>
>>
>>
>>
>>On Wednesday, November 27, 2013 5:49 PM, arun <smartpink...@yahoo.com> wrote:
>>
>>
>>
>>Hi,
>>
>>lst1[[1]][,2] <- NA
>>lst2 <- lapply(lst1,function(x) summary(lm(rate~.,data=x)))
>>Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) :
>> 0 (non-NA) cases
>>
>>
>>
>>lst2 <- lapply(lst1[sapply(lst1,function(x)
>>!(all(rowSums(is.na(x))>0)))],function(x) summary(lm(rate~.,data=x)) )
>>A.K.
>>
>>
>>
>>Hi,
>>
>>thank you for help. :-)
>>
>>I applied your script to the data but I have got the error:
>>
>>Error
>>in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) : 0
>>(non-NA) casesI forget to write that some of the data are NA.
>>
>>I executed this code:
>>
>>lst1 <- split(data[,-16],data[,16])
>>>any(sapply(lst1,nrow)!=123)
>>>#[1] FALSE
>>>lst2
>><- lapply(lst1,function(x)
>>summary(lm(rate~cap.log+liqamih.log+pbv,data=x))) # here I can set the
>>dependent variables if I want to test different versions of the model
>>(e.g with only e dependent variables), right?
>>>length(lst2)
>>>#[1] 334
>>>
>>
>>
>>
>>
>>
>>On Wednesday, November 27, 2013 5:27 PM, arun <smartpink...@yahoo.com> wrote:
>>Hi,
>>Try:
>>set.seed(49)
>>dat1 <-
>>as.data.frame(matrix(sample(c(NA,1:50),41082*15,replace=TRUE),ncol=15))
>> dat1$indx <- as.numeric(gl(334*123,123,334*123))
>>names(dat1)[1] <- "rate"
>> lst1 <- split(dat1[,-16],dat1[,16])
>>any(sapply(lst1,nrow)!=123)
>>#[1] FALSE
>>lst2 <- lapply(lst1,function(x) summary(lm(rate~.,data=x)))
>> length(lst2)
>>#[1] 334
>>
>>A.K.
>>
>>Hi all!
>>
>>I am very beginner in R so please excuse me some of the naive questions. I am
>>learning.
>>Here is description of my problem:
>>
>>I have database (in single csv file)
>> characteristic_1 characteristic_2 ...
>> characteristic_49
>>subject_1 | c1_1_t=1 | c2_1_t=1 ... |
>>c49_1_t=1
>>subject_2 | c1_2_t=1 | c2_2_t=1 ... |
>>c49_2_t=1
>>subject_3 | c1_3_t=1 | c2_3_t=1 ... |
>>c49_3_t=1
>>...
>>subject_334 | c1_334_t=1 | c2_334_t=1 ... |
>>c49_334_t=1
>>subject_1 | c1_1_t=2 | c2_1_t=2 ... |
>>c49_1_t=2
>>subject_2 | c1_2_t=2 | c2_2_t=2 ... |
>>c49_2_t=2
>>subject_3 | c1_3_t=2 | c2_3_t=2 ... |
>>c49_3_t=2
>>...
>>subject_334 | c1_3_t=2 | c2_3_t=2 ... |
>>c49_3_t=2
>>
>>and so on ... till t (time) = 123
>>
>>so I have 334 subjects with 49 characteristics measured in 123 points of time.
>>
>>I would like to run 123 regressions (three kinds: lm, rlm and
>>lmrob - for comparison reasons) each one for 334 subjects and 49
>>dependent variables and after each regression (actually after conducting
>>each of the three regressions:lm, rlm and lmrob) I would like to save
>>txt (or csv) file with results (summary) and some test* (each regression
>>can be named reg_1, reg_2 ... reg_123) for those regressions.
>>
>>To make things more clear:
>>regressions would look like that:
>>
>>summary(lm(rate~cap.log+liqamih.log+liqwol.log+pbv.log+mom.log+
>> +beta.wig+beta.wig.eq
>> +beta.sp
>> +beta.wig.macro
>> +beta.sp.macro
>> +beta.sentim.pl+beta.sentim.pl.ort
>> +beta.sentim.usa+beta.sentim.usa.ort, data=data))
>>
>>the problem is how to make this lm() above for "rolling window"
>>id est for first 334 observations? (total observations: 123*334) and so
>>on.
>>I need to run regression_1 for first 334 observations, regression_2
>>for next 334 obs (from 335 to 669) and so on till regression_123 (from
>>last 40748 till 41082).
>>And each time I run such regression I would like to save results (summary and
>>mentioned tests).
>>
>>Then I would like to repeat the same procedure but for rlm() and lmrob() if
>>possible.
>>
>>I think I can write "tests" part of the script alone (could you
>>write me some comments where exactly I should put it in script to have
>>the test automatically repeated the results saved), but 'saving' and
>>'repeating 123 times' procedures are quite complicated for me, at least
>>now. So here I am asking for help with it.
>>
>>In the end I would like to have three txt (or csv) files:
>>one containing 123 "summaries" and test results of lm,
>>one containing 123 "summaries" and test results of rlm
>>and one containing 123 "summaries" and test results of lmrob.
>>
>>Could someone help me with this task?
>>I am grateful for your help and support.
>>
>>________________
>>*like:
>>jarque.bera.test()
>>vif()
>>ncvTest()
>>durbinWatsonTest()
>>
>>---some of them are not applicable for rlm and lmrob - so in
>>this case I would like to have "test NA" in the three output txt (or
>>csv) files
>>Some of them are also not applicable to cross-sectional regressions
>>... but still I would like to keep them in script for later
>>modifications
>>
>
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