similar to: two simple questions about MCMCpoissonChange

Thank you Rui for your code. I basically understood all your suggestions. I am using an old version of R (version 3.6.3, installed in a server I am not allowed to control), and the new pipe operator does not work. I tried to run your code without the "|>" operator, but I get an error when I use apply. Could you please expand your code without the pipe operator? Thank you again

I would like to simulate some SARIMA models, e.g. a SARIMA (1,0,1)(1,0,1)[4] process. I installed the package 'forecast', where the function simulate.Arima should do what I am trying to do. I am not able to understand how it works Could somebody help me with an example? thank you Stefano Sofia AVVISO IMPORTANTE: Questo messaggio di posta elettronica pu? contenere informazioni

Dear list users, if within a function I first define a matrix mymat <- matrix(NA, nrow=m, ncol=n) and somewhere afterwards by mistake mymat <- c(1,2,3) this second command deletes the first one. How can I make sure that within the function mymat will always remain the matrix defined at the beginning, without possibility of changing it throughout the code? Secondly, is it possible to define

Should not the result be NULL if you have removed the NA with na.rm=TRUE ? B. > On Mar 21, 2018, at 11:44 AM, Stefano Sofia <stefano.sofia at regione.marche.it> wrote: > > Dear list users, > let me ask you this trivial question. I worked on that for a long time, by now. > Suppose to have a data frame with NAs and to sum some columns with rowSums: > > df <-

Dear R-list users, this question is not strictly related to R, but hopefully somebody will be able to answer. In a schematic way, which is the algorithm to sample from a multivariate normal distribution using the singular value decomposition? thank you for your help Stefano AVVISO IMPORTANTE: Questo messaggio di posta elettronica pu? contenere informazioni confidenziali, pertanto ? destinato

Dear R users, I am trying to use the dlm package, and in particular the dlmBSample function. For some reason that I am not able to understand, this function does not work properly and the plot of the result does not make sense, while dlmFilter works perfectly. I think that my_mod is correct, because the output of my_dlmFilter$mod is fine. Where is my mistake or my misunderstanding? This is the

On 21/03/2018 11:44 AM, Stefano Sofia wrote: > Dear list users, > let me ask you this trivial question. I worked on that for a long time, by now. > Suppose to have a data frame with NAs and to sum some columns with rowSums: > > df <- data.frame(A = runif(10), B = runif(10), C = rnorm(10)) > df[1, ] <- NA > rowSums(df[ , which(names(df) %in%

Dear R users, I have difficulty to create a list within a list. Example: with > A <- vector(mode="list", 4) I create a list of 4 elements: > A [[1]] NULL [[2]] NULL [[3]] NULL [[4]] NULL In each element of this list I can store, for example, a matrix: A[[1]] <- matrix ... I need each element of A to be a list (all the lists of the same length), and then store matrices

Thank you to Ozgur, who gave me the hints for an easy solution. There are the commands that work for my case: mean(my_dataframe$Freq[my_dataframe$month == 5 & my_dataframe$day %in% c(1:7)]) mean(my_dataframe$Freq[my_dataframe$month == 5 & my_dataframe$day %in% c(8:14)]) ... Stefano Sofia PhD This is the original message: Dear list users, I have a data frame as below specified. From

Dear Jim and dear Enrico, thank you for your replies. Unfortunately your hints didn't solve my problem, and I am getting mad. Can I show you my whole process? I will be as quick as possible. I start from a data frame called Snow of the form year month day hh mm hs 2007 11 19 0 0 0.00 2007 11 19 0 30 0.00 2007 11 19 1 0 0.00 2007 11 19 1 30 0.00 2007 11 19 2 0 0.00 2007 11 19 2 30 0.00 2007 11

Dear R list users, the singluar value decomposition of a symmetric matrix M is UDV^(T), where U = V. La.svd(M) gives as output three elements: the diagonal of D and the two orthogonal matrices u and vt (which is already the transpose of v). I noticed that the transpose of vt is not exactly u. Why is that? thank you for your attention and your help Stefano AVVISO IMPORTANTE: Questo messaggio di

Dear R-users, suppose I have three dataframes like these df1: mydate min_temp 31032013 12 01042013 8 02042013 -999 df2: mydate min_temp 31032013 10 01042013 11 02042013 14 df3: mydate min_temp 31032013 4 01042013 3 02042013 5 where -999 means that the temperature data is not available (at the moment I cannot change it to NA because I am not the db administrator); suppose also that oggi is

Dear list users, I have a data frame as below specified. From the 1st of May to the 30th of September of several years (e.g. from 2004 to 2011) I have a frequency of accidents. I need the mean of accidents divided by weeks (i.e. the mean of accidents from the 1st to the 7th of May of all the years, from the 8th to the 14th of May, ..., from the 29th to the 31st of May, from the 1st to the 7th of

Hi Stefano, As the help page says: "The default for the format methods is "%Y-%m-%d %H:%M:%S" if any element has a time component which is not midnight, and "%Y-%m-%d" otherwise. This is because when the result is printed, it uses the default format. If you want a specified output representation: format(strptime(init_day, format="%Y-%m-%d-%H-%M"),"%Y-%M-%d

Surely the result of summation of non-existent values is not defined, is it not? And since the NA values have been _removed_, there's nothing left to sum over. In fact, pretending the the result in that case is zero would appear audacious, no? Cheers, Boris > On Mar 21, 2018, at 12:58 PM, Jeff Newmiller <jdnewmil at dcn.davis.ca.us> wrote: > > What do you mean by

Dear list users, I have to aggregate wind direction data (wd) using a function that requires also a second input variable, wind speed (ws). This is the function that I need to use: my_fun <- function(wd1, ws1){ u_component <- -ws1*sin(2*pi*wd1/360) v_component <- -ws1*cos(2*pi*wd1/360) mean_u <- mean(u_component, na.rm=T) mean_v <- mean(v_component, na.rm=T) mean_wd

Dear R-list users, >From an initial and a final date I create a sequence of days using POSIXct. If this interval covers all or only in part the months from May to October, I need to get rid of the days from the 2nd of May to the 31st of October: a <- as.POSIXct("2002-11-01", format = "%Y-%m-%d", tz="Etc/GMT-1") b <- as.POSIXct("2004-06-01",

?s 15:51 de 13/05/2023, Stefano Sofia escreveu: > Dear list users, > > I have to aggregate wind direction data (wd) using a function that requires also a second input variable, wind speed (ws). > > This is the function that I need to use: > > > my_fun <- function(wd1, ws1){ > > u_component <- -ws1*sin(2*pi*wd1/360) > v_component <-

?s 16:23 de 28/05/2024, Stefano Sofia escreveu: > Dear R-list users, > > From an initial and a final date I create a sequence of days using POSIXct. > > If this interval covers all or only in part the months from May to October, I need to get rid of the days from the 2nd of May to the 31st of October: > > > a <- as.POSIXct("2002-11-01", format =

I see: consistency with additive identity. That makes sense. Thanks. B. > On Mar 21, 2018, at 1:22 PM, peter dalgaard <pdalgd at gmail.com> wrote: > > No. The empty sum is zero. Adding it to another sum should not change it. Nothing audacious about that. This is consistent; other definitions just cause trouble. > > -pd > >> On 21 Mar 2018, at 18:05 , Boris