similar to: lmer Error message

Assuming the input data.frame, DF, is of the form shown reproducibly in the Note below, to convert the series to zoo or ts: library(zoo) # convert to zoo z <- read.zoo(DF) # convert to ts as.ts(z) # Note: DF <- structure(list(year = c(1980, 1981, 1982, 1983, 1984), cnsm = c(174, 175, 175, 172, 173), incm = c(53.4, 53.7, 53.5, 53.2, 53.3), with = c(60.3, 60.5, 60.2, 60.1, 60.7)),

You can just use the same code that I provided before but now use your dataset. Like this df <- read.csv(file="data2.csv",header=TRUE) dates <- as.Date(paste(df$year,"-01-01",sep="")) myXts <- xts(df,order.by=dates) head(myXts) #The last command "head(myXts)" shows you the first few rows of the xts object year cnsm incm wlth

oky.. thank you very much to all of you On Sat, Sep 16, 2017 at 2:06 PM, Eric Berger <ericjberger at gmail.com> wrote: > You can just use the same code that I provided before but now use your > dataset. Like this > > df <- read.csv(file="data2.csv",header=TRUE) > dates <- as.Date(paste(df$year,"-01-01",sep="")) > myXts <-

> > Hi all, > I have a vector xm say: xm = c(1,2,3,4,5,5,5,6,6) > > I want to return a vector with the corresponding probabilities based on the > amount of times the numbers occurred. For example, I should get the > following vector for xm: > prob.xm = c(1/9, 1/9, 1/9, 1/9, 3/9, 3/9, 3/9, 2/9, 2/9) > Using prop.table gives: Usage (with table) > prob.xm <-

> On 15 Sep 2017, at 11:38, yadav neog <yadavneog at gmail.com> wrote: > > hello to all. I am working on macroeconomic data series of India, which in > a yearly basis. I am unable to convert my data frame into time series. > kindly help me. > also using zoo and xts packages. but they take only monthly observations. > > 'data.frame': 30 obs. of 4 variables:

> On 15 Sep 2017, at 12:38, yadav neog <yadavneog at gmail.com> wrote: > > hello to all. I am working on macroeconomic data series of India, which in > a yearly basis. I am unable to convert my data frame into time series. Do you really need to convert your data to time series/xts/zoo? I don?t know you try what kind of an analysis but perhaps you don?t have to. > kindly

hello to all. I am working on macroeconomic data series of India, which in a yearly basis. I am unable to convert my data frame into time series. kindly help me. also using zoo and xts packages. but they take only monthly observations. 'data.frame': 30 obs. of 4 variables: $ year: int 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 ... $ cnsm: num 174 175 175 172 173 ... $ incm:

Hallo, I would like to add the marginal distributions along the X and the Y axis to a scatter plot. Can anybody help me, please? Thank you, Paolo -- Paolo Bulla Istituto di Metodi Quantitativi Universit?? "L. Bocconi" viale Isonzo 25 20136 Milano paolo.bulla at unibocconi.it

> On 15 Sep 2017, at 11:38, yadav neog <yadavneog at gmail.com> wrote: > > hello to all. I am working on macroeconomic data series of India, which in > a yearly basis. I am unable to convert my data frame into time series. > kindly help me. > also using zoo and xts packages. but they take only monthly observations. > > 'data.frame': 30 obs. of 4 variables:

Hello anyone, I'm trying to install R on Mandriva 2006 distribution via rpm file with the line urpmi R-2.0.0-1mdk.i586.rpm but I got an error message saying that the file is not accessible due to some info problem. I also tried with a source code in R-2.1.1.tar but I think that there is some problem concerning the new version of gcc (4.x), so I downgraded it to gcc 3.4.5 but it does

Hello, I have to compute a multiple summation (not an integration because the independent variables a are discrete) for all the values of a function of several variables f (x_1,...,x_n), that is sum ... sum f(x_1,...,x_n) x_1 x_n have you some suggestion? Is it possible? I know that for multiple integration there is the function adapt, but it has at most n=20. In my case n depends on the

thankx to everyone for your valuable suggestions. one query regarding the GARCH model. I have applied the GARCH model for the same data that I send you all . and my results coming like Error in .sgarchfit(spec = spec, data = data, out.sample = out.sample, : ugarchfit-->error: function requires at least 100 data points to run can you suggest something on it. On Fri, Sep 22, 2017 at 6:02

Dear all, I have a so large image (43,000 x 18,000 pixels) and I need clip this image with a smallest one (1000x1000 pixels). I can read the second image using rgdal package. But the first image can´t be read on my system because if memory limitation (I have about 2GB availabe). So I would like hear from you if anyone have some suggestin in this regards. I have also ArcGis 8.6 ans Erdas 8.3

Dear R users: I have a dataset with two variables (>20000 observations, two samples from same subject) and I used "kernSur" from library(Genkern) to get a estimated bivariate density and corresponding plots as follows: new.data.normal<-data.normal[!is.na(data.normal[,2]),] x<-new.data.normal[,2] y<-new.data.normal[,3] op <- KernSur(x,y, xgridsize=50, ygridsize=50,

Hi, I am looking for an efficient way to compute the values of the density function of a multivariate T distribution - something like "dmvnorm", but for T distr. Does this exist somewhere? Many thanks, Jan Bulla Goettingen University

Apologies for the empty post that went to the list... On ??????, ???????????????????? 28, 2005 9:11, Paolo Bulla wrote: > Hello anyone, > I'm trying to install R on Mandriva 2006 distribution via rpm file with the > line > urpmi R-2.0.0-1mdk.i586.rpm ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ This is an older rpm that Michele Alzeta contributed for Mandrake 10.0 (and that was a long time

Hi, I was wondering why anova() and drop1() give different tail probabilities for F tests. I guess overdispersion is calculated differently in the following example, but why? Thanks for any advice, Tom For example: > x<-c(2,3,4,5,6) > y<-c(0,1,0,0,1) > b1<-glm(y~x,binomial) > b2<-glm(y~1,binomial) > drop1(b1,test="F") Single term deletions Model: y ~

the data is : >table.8.3<-data.frame(expand.grid( marijuana=factor(c("Yes","No"),levels=c("No","Yes")), cigarette=factor(c("Yes","No"),levels=c("No","Yes")), alcohol=factor(c("Yes","No"),levels=c("No","Yes"))), count=c(911,538,44,456,3,43,2,279))

I would like to do a SS type III analysis on a proportional odds logistic regression model. I use drop1(), but dropterm() shows the same behaviour. It works as expected for regular main effects models, however when the model includes an interaction effect it seems to have problems with matching the parameters to the predictor terms. An example: library("MASS"); options(contrasts =

I am using R to teach, and here are a couple of things that I thought would work didn't work. 1. I noticed the utility data(***,package=***) recently and like it very much, but unless I type in the whole word "package" I'll get an error in 1.4.0. For example, data(cats,package=MASS) works fine but data(cats,pac=MASS) doesn't. 2. drop1 doesn't seem to be as smart as