similar to: Fit continuous distribution to truncated empirical values

Dear friends, I have a weekly time series which starts on Jan 4th, 2003 and ends on december 31st, 2016. I set up my ts object as follows: MyTseries <- ts(mydataset, start=2003, end=2016, frequency=52) MyModel <- auto.arima(MyTseries, d=1, D=1) MyModelForecast <- forecast (MyModel, h=12) Since my last observation was on december 31st, 2016 I expected my forecast date to start on

Hi, I would appreciate if somebody could help me with following calculation. I have a dataframe, by 10 minutes time, for mostly one year data. This is small example: > dput(test) structure(list(jul = structure(c(14655, 14655, 14655, 14655, 14655, 14655, 14655, 14655, 14655, 14655, 14655, 14655, 14655, 14655, 14655, 14655), origin = structure(0, class = "Date")), time =

> On Dec 6, 2017, at 5:07 AM, Paul Bernal <paulbernal07 at gmail.com> wrote: > > Dear friends, > > I have a weekly time series which starts on Jan 4th, 2003 and ends on > december 31st, 2016. > > I set up my ts object as follows: > > MyTseries <- ts(mydataset, start=2003, end=2016, frequency=52) > > MyModel <- auto.arima(MyTseries, d=1, D=1)

Thank you very much David. As a matter of fact, I solved it by doing the following: MyTimeSeriesObj <- ts(MyData, freq=365.25/7, start=decimal_date(mdy("01-04-2003"))) After doing that adjustment, my forecasts dates started from 2017 on. Cheers, Paul 2017-12-06 12:03 GMT-05:00 David Winsemius <dwinsemius at comcast.net>: > > > On Dec 6, 2017, at 5:07 AM, Paul

Hey everyone, I am an R-newby... so sorry for bothering you with simple-to-solve questions;) I have the following issue: trying to add labels to my scatterplots (with geom_dl in ggplot2). Everything works fine, but after checking every resource I do not find a way to change the font size of my labels. I tried size, cex, fontsize at every position... but it always stays the same. ggplot()+

Dear arun and all R users, I will first of all try to simply define my issue.. I have data in the following format Year Discharge dd/mm/yyyy x .. … … … There are some NA values in the discharge which I would like to predict by using “predict command”. I cant figure out the way to write the coding for that. Could you please help me on that??? I have also ,written

R experts, I am working with a fairly large data set comprised of 563 rows by 116 columns including several different modes. I have been unable to read in the data set completely using the read.table function and the RGui (i.e. nearly half the total number of rows are missing from the data set along with the column names). The data does read in fully using Tinn-R's Rterm; however, at several

Hello, I have a pedigree file such this: FAMID ID FA ID MO ID SEX STATUS 1 1 0 0 2 0 1 2 3 1 2 2 1 4 3 1 1 2 1 5 3 1 1 0 1 6 3 1 1 0 1 7 3 1 2 2 1 8 3 1 1 0 1 9 3 1 1 0 1 10 3 1 2 0 1 11 3 1 1 0 1 3 0 0 1 0 2 12 13

Hi, I'm analyzing a large number of large simulation datasets, and I've isolated one of the bottlenecks. Any help in speeding it up would be appreciated. `dat` is a dataframe of samples from a regular grid. The first two columns are the spatial coordinates of the samples, the remaining 20 columns are the abundances of species in each cell. I need to calculate the species richness in

R experts, How could I extract the week number from a date vector (in Date class) such that week numbering (week 1...2...) begins (May 01) and ends (October 31) on the same specific dates each year? Week numbering must conform to the following day numbering format (Sat=1,Sun=2,Mon=3.....Fri=7). This means that new weeks must begin on Saturdays, and end on Fridays (except for the first date

Hello, Two lapply questions (system info and sample data below): 1) Why does the first form of command1 add the name of y _after_ the str() output rather than before as does the second (preferred) form? # command1 version1 invisible(lapply(ls(pattern='bn'), function(y) cat(y, "\n", str(get(y)), "\n") )) # command1 version2 (preferred output)

Hello, I'm running into a very strange problem: > xrange <- c(-2.5,2.5) > xdim <- 100 > mobility <- 0.1 > slope <- 1.16 > urange <- slope*xrange > udim <- max(slope*xdim,5) > du <- (urange[2]-urange[1])/udim > uvec <- urange[1]+(1:udim-0.5)*du > # type dependent weight function > ckern <-

Dear R users, I created a matrix that tells me the first day of use of a category by id. #Calculate time difference test$tdiff<-as.numeric(difftime(as.Date("2002-09-01"), test$ftime, units = "days")) # obtain the index date per person and dcategory index.date.test<-tapply(test$tdiff, list(test$id, test$rcat), max) Nonetheless, at the moment I think will be

R users, I have been trying to write a program in R that will extract rows from a data frame and combine the rows into a new smaller data frame while meeting several criteria. I would greatly appreciate any advice that could help me get started down the right path. What I want to do is to extract two rows WEEK (26 weeks total) from the data frame by sampling without replacement from the

I have a dataframe of animal locations that I need to have in incremental order so that I can calculate the distance traveled between each time step. However, I have identified a few values that don't seem to sort properly. For instance, the last value in the table below should be the first value after sorting, since its time value is '00:01:35'. But, for some reason, it seems to be

https://bugzilla.samba.org/show_bug.cgi?id=11558 Bug ID: 11558 Summary: rsync always try change owner and group of symlink in --fake-super mode Product: rsync Version: 3.1.2 Hardware: x64 OS: Linux Status: NEW Severity: normal Priority: P5 Component: core

Hi, I have just started using R. Now I have the following problem: I want to create an Empirical Cumulative Distribution Function and I only came so far: F10 <- ecdf(x) plot(F10, verticals= TRUE, do.p = TRUE, lwd=3) x=c(1.6,1.8,2.4,2.7,2.9,3.3,3.4,3.4,4,5.2) Now I'd like to use arguments such as xlabs and main but I don't know how to integrate them. I hope someone can help me, I am

Hi, I would like to implement the empirical copula in R, does anyone know if it is included in a package? I know it is not in the "Copula" package. This one only includes a gof-test based on the empirical copula process. Thanks for your help! Gregor -- View this message in context: http://www.nabble.com/Empirical-copula-in-R-tf4018319.html#a11412335 Sent from the R help mailing list

Is it possible to get the empirical (sandwich) S.E. estimates for the fixed effects in lme () (thus allowing possibly correlated errors within the group)? In SAS you can get it by the 'empirical' option to PROC MIXED. Cheers, Michael -- Na (Michael) Li, Ph.D. Division of Biostatistics A443 Mayo Building, MMC 303 School of Public Health 420 Delaware

Hello, I wanted to ask if there is an R package to fit GLM (logistic for example) via empirical likelihood. -- -Tony [[alternative HTML version deleted]]