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Hi, I am trying to the data from https://online.stat.psu.edu/onlinecourses/sites/stat501/files/ch15/employee.txt without any success. Below is the error I am getting: > read.delim('https://online.stat.psu.edu/onlinecourses/sites/stat501/files/ch15/employee.txt') Error in make.names(col.names, unique = TRUE) : invalid multibyte string at '<ff><...

...cated big-endian then the file decoding would break. If there is a BOM, don't override it unless you have to (e.g. for a wrong BOM)... leave off the LE unless you really need it. That sounds like good advice, but it doesn't work: > read.delim( + 'https://online.stat.psu.edu/onlinecourses/sites/stat501/files /ch15/employee.txt', + fileEncoding = "UTF-16" + ) [1] time [2] vendor.?????........??........?.??........?.??.?..?.....?..?..?...?.?..?..?...?.??....?...?.??. and so on. > > On September 7, 2024 1:22:23 PM PDT, Enr...

...BOM)... leave off the LE unless you really need it. On September 7, 2024 1:22:23 PM PDT, Enrico Schumann <es at enricoschumann.net> wrote: >On Sun, 08 Sep 2024, Christofer Bogaso writes: > >> Hi, >> >> I am trying to the data from >> https://online.stat.psu.edu/onlinecourses/sites/stat501/files/ch15/employee.txt >> without any success. Below is the error I am getting: >> >>> read.delim('https://online.stat.psu.edu/onlinecourses/sites/stat501/files/ch15/employee.txt') >> >> Error in make.names(col.names, unique = TRUE) : >>...

...hen the file decoding would break. If there is a BOM, don't override it unless you have to (e.g. for a wrong BOM)... leave off the LE unless you really need it. > >That sounds like good advice, but it doesn't work: > > > read.delim( > + 'https://online.stat.psu.edu/onlinecourses/sites/stat501/files /ch15/employee.txt', > + fileEncoding = "UTF-16" > + ) > [1] time > > > > > > > > > > > > > > [2] vendor.?????........??........?.??........?.??.?..?.....?..?..?...?.?..?..?...?.??....?...?.??. > >and so...

On Sun, 08 Sep 2024, Christofer Bogaso writes: > Hi, > > I am trying to the data from > https://online.stat.psu.edu/onlinecourses/sites/stat501/files/ch15/employee.txt > without any success. Below is the error I am getting: > >> read.delim('https://online.stat.psu.edu/onlinecourses/sites/stat501/files/ch15/employee.txt') > > Error in make.names(col.names, unique = TRUE) : > > invalid multibyt...

That looks like a UTF-16LE byte order mark. Simply open the connection with the proper encoding: read.delim( 'https://online.stat.psu.edu/onlinecourses/sites/stat501/files/ch15/employee.txt', fileEncoding = "UTF-16LE" ) On Sat, Sep 7, 2024 at 3:57?PM Christofer Bogaso <bogaso.christofer at gmail.com> wrote: > > Hi, > > I am trying to the data from > https://online.stat.psu.edu/onlinecourses/sites/stat501/fil...

...g would break. If there is a BOM, don't override it unless you have to (e.g. for a wrong BOM)... leave off the LE unless you really need it. >> >> That sounds like good advice, but it doesn't work: >> >>> read.delim( >> + 'https://online.stat.psu.edu/onlinecourses/sites/stat501/files /ch15/employee.txt', >> + fileEncoding = "UTF-16" >> + ) >> [1] time >> >> >> >> >> >> >> >> >> >> >> >> >> >> [2] vendor.?????........??........?.??........?....

Dear all, can somebody give me some pointer how I can fit a "linear-by-linear association model" (i.e. loglinear model for the ordinal variables) in R? A brief description can be found here 'https://onlinecourses.science.psu.edu/stat504/node/141'. Thanks for your help

Dear all, I am facing some problem with how to fit a "Baseline category Logit model" with R. Basically I am considering famous "Alligator" data as discussed by Agresti. This data can also be found here: https://onlinecourses.science.psu.edu/stat504/node/174 (there is also an accompanying R file, however the underlying R code could not load the data properly!!!) Below are the stuffs what I have done so far: My_Data <- structure(list(Number = c(7L, 4L, 1L, 0L, 0L, 0L, 0L, 1L, 5L, 2L, 16L, 3L, 3L, 0L, 2L, 1L, 2L, 2L,...

Hi all, I have two time series that I would like to correlate but as they are autocorrelated, I am "pre-whitening" them first by fitting ARIMA models, then correlating their residuals....as described in https://onlinecourses.science.psu.edu/stat510/?q=node/75 However, http://www.stat.pitt.edu/stoffer/tsa2/Rissues.htm discusses some issues with ARIMA in R. In particular, for issue 2, if there is any differencing, a constant term is not included, but the solution is to 1) input a series that has already been differenced...