similar to: Time-series moving average question

My guess would be that if you inspect the output from ma(dat3[1:28], order=3) you will find some NAs in it. And then forecast() doesn't like NAs. But I can't check, because I can't find the ma() and forecast() functions. I assume they come from some package you installed; it would be helpful to say which package. -Don -- Don MacQueen Lawrence Livermore National Laboratory 7000

Hi Don, wow, you are so right. I picked that piece up from the bloggers tutorial and since I am R naive yet, I thought it was all one step moving_average = forecast(ma(tdat[1:31], order=2), h=5) Truly, I usually print and check at every step I can, as painful as it is sometimes. Great lesson for this novice usR. So the first and last values are NA in each case? Do you know why? Should I replace

You are right that there are no NAs in the practice data. But there are NAs in the moving average data. To see this, break your work into two separate steps, like this: tnr.ma <- ma(dat3[1:28], order=3) TNR_moving_average <- forecast(tnr.ma, h=8) I think you will find that the warning comes from the second step. Print tnr.ma and you will see some NAs. -Don -- Don MacQueen Lawrence

Dear All, I am trying to use the function ses from the forecast package. >From its help I have : Usage: ses(y, h = 10, level = c(80, 95), fan = FALSE, initial = c("optimal", "simple"), alpha = NULL, lambda = NULL, biasadj = FALSE, x = y, ...) My query is that if I do not mention the initial value will its default value be "optimal". A MWE would be

The first one, i.e. "optimal"; check help for match.arg() for the idiom. -pd > On 2 Oct 2017, at 11:48 , Ashim Kapoor <ashimkapoor at gmail.com> wrote: > > Dear All, > > I am trying to use the function ses from the forecast package. > > From its help I have : > > Usage: > > ses(y, h = 10, level = c(80, 95), fan = FALSE, initial =

Instead of Tsp = c(2016, 2018, 12) try Tsp = c(2016, 2018.25, 12) Hence, you can specify the object as structure(c(5973156.76, 5159011.2, 6695766.64, 6365359, 6495218.53, 7226302.39, 6835272.7, 7383501.57, 6962748.19, 7623278.72, 7274994.33, 7919421.8, 7360740.81, 7436693.35, 8545765.55, 7337269.76, 8180585.44, 8376635.05, 7758261.24, 10374641.22, 8000314.11, 9114958.9, 9805149.15,

Hello Don, thank you for your response. I appreciate your help. I am using the forecast package, originally I found it following a forecasting example on bloggers.com https://www.r-bloggers.com/time-series-analysis-using-r-forecast-package/ And subsequently located the complete pdf https://cran.r-project.org/web/packages/forecast/forecast.pdf Since I created this practice data using the

Hi. I am trying to follow this forecasting tutorial at: https://www.r-bloggers.com/basic-forecasting/ Using my own data, I cannot get past the first step, lots of laughs. dat3 <- structure(c(5973156.76, 5159011.20, 6695766.64, 6365359.00, 6495218.53, 7226302.39, 6835272.70, 7383501.57, 6962748.19, 7623278.72, 7274994.33 ,7919421.80, 7360740.81, 7436693.35,

I have a series of animals that are being radio-tracked. I have written some code that goes through each animal and calculates the total distance that each animal is traveling. I will need to run these data on a regular basis and want to write the result to a .php webpage file so that the page updates automatically when I re-run the code. I thought I'd be able to use the

Hi again. Perhaps a simple question this time.... I am analysing data with a dependent variable of insect counts, a fixed effect of site and two random effects, day, which is the same set of 10 days for each site, and then transect, which is nested within site (5 each). I am trying to fit the cross classified model using GLMM in lme4. I have, for potential use, created a second coding

hi... i am a phd student using r. i am having difficulty plotting average effects. admittedly, i am not really understanding what each of the commands mean so when i get the error i am not sure where the issue is. here is my code... i will include the points at which there are errors.... > dat2 <- dat3 <- dat > dat2$popc100 <- dat2$popc100 + 1000 >

Can somebody tell me that, if I do some arithmetic calculation over 2 matrices then how the column names and row names are preserved? It seems that, for multiplication, column names and row names of the 2nd matrix are preserved and for additional, there seems not having any explicit rule: > set.seed(1) > dat1 <- matrix(rnorm(25), 5); colnames(dat1) = rownames(dat1) =

I've been trying with no success to model mixtures of Gamma distributions using the package flexmix (see examples below). Can anyone help me get it to model better? Thanks very much. -Ben ## ## Please help me get flexmix to correctly model mixtures of ## Gamma distributions. See examples below. ## library('flexmix') ## ## Plot a histogram of dat and the Gamma mixture model given

Hi, Try: dat2<- read.csv("BOlValues.csv",header=TRUE,sep="\t",row.names=1) dim(dat2) #[1] 20 28 indx2<-expand.grid(names(dat2),names(dat2),stringsAsFactors=FALSE) nrow(indx2) #[1] 784 indx2New<- indx2[indx2[,1]!=indx2[,2],] nrow(indx2New) #[1] 756 res2<-sapply(seq_len(nrow(indx2New)),function(i) {x1<- indx2New[i,];

Ira, obj_name<- load("arun.RData") Pred1<- get(obj_name[1]) Actual1<- get(obj_name[2]) dat2<- data.frame(S1=rep(Pred1[,1],ncol(Pred1)-1),variable=rep(colnames(Pred1)[-1],each=nrow(Pred1)),Predict=unlist(Pred1[,-1],use.names=FALSE),Actual=unlist(Actual1[,-1],use.names=FALSE),stringsAsFactors=FALSE) dat2New<- dat2[!(is.na(dat2$Predict)|is.na(dat2$Actual)),] ?dat3<-

Hi, From your example data, dat1<- read.table(text=" id1?? id2?? value a????? b?????? 10 c????? d??????? 11 b???? a???????? 10 c????? e???????? 12 ",sep="",header=TRUE,stringsAsFactors=FALSE) #it is easier to get the output you wanted dat1[!duplicated(dat1$value),] #? id1 id2 value #1?? a?? b??? 10 #2?? c?? d??? 11 #4?? c?? e??? 12 But, if you have cases like the one

HI, You can do this in many ways: dat1<-read.table(text=" med1,med2,med3???? ?1,0,1?????? 0,1,1??? 2,0,0 ",sep=",",header=TRUE)?? #1st method library(reshape) dat2<-melt(dat1) dat3<-aggregate(dat2$value,by=list(dat2$variable),sum) ?colnames(dat3)<-c("name","sum(n11)") ?dat3 #? name sum(n11) #1 med1??????? 3 #2 med2??????? 1 #3 med3??????? 2

Dear Everybody: I'm doing my usual "how does that work in R" thing with some Stata projects. I find a gross gap between the Stata and R in Cox PH models, and I hope you can give me some pointers about what goes wrong. I'm getting signals from R/Survival that the model just can't be estimated, but Stata spits out numbers just fine. I wonder if I should specify initial

Hi, May be you can try this: dat1New<-? dat1[!(duplicated(dat1$gene)|duplicated(dat1$gene,fromLast=TRUE)),] dat2<-dat1[duplicated(dat1$gene)|duplicated(dat1$gene,fromLast=TRUE),] ?lst1<-split(dat2,dat2$gene) dat3<-unsplit(lapply(lst1,function(x) {x1<- sum(apply(x[,6:32],2,function(y) y[1]>=y[2]));x2<- sum(apply(x[,6:32],2, function(y) y[1]<=y[2])); if(x1>x2) x[1,] else

Hi all Say I have a function: myname=function(dat,x=5,y=6){ res<<-x+y-dat } for various input such as myname(dat1) myname(dat2) myname(dat3) myname(dat4) myname(dat5) how should I modify the 'res' line, to have new informative variable name correspondingly, such as dat1.res dat2.res dat3.res dat4.res dat5.res stored in the workspace. This is only an example of a complex