similar to: Bug? in summary( ) function base package

I have weekly time series data with year, month, day, and price variables. The input data set for the weekly series takes the following form: Year month day price 1990 8 20 119.1 1990 8 27 124.5 1990 9 3 124.2 1990 9 10 125.2 1990 9 17 126.6 1990 9 24 127.2 1990 10 1 132.1 1990 10 8 133.3 1990 10 15 133.9 1990 10 22 134.5 1990 10 29 133.9 .. ... ... ... ... ... .... .... 2008 3 3 313.7 2008

I have an ascii data set of monthly observation starting in Jan 1946 with a header. hstarts 57 65 95 103 103 97 94 . . . Which I read with the following code tab6.1<-ts(read.table(fname, header=TRUE),frequency=12,start=c(1946,1)) I would like to run a time series model with dummy variables for each month. If I had a variable which take values from 1 to 12 indicating the month I could use

I would like to read the following hierarchical data set. There is a family record followed by one or more personal records. If col. 7 is "1" it is a family record. If it is "2" it is a personal record. The family record is formatted as follows: col. 1-5 family id col. 7 "1" col. 9 dwelling type code The personal record is formatted as follows: col.

Is anyone aware of an R procedure similar to STATA's "heckprob" procedure? "Heckprob" fits maximum likelihood probit models correcting for sample selection bias. Thanks, Richard Saba Department of Economics Auburn University Email: sabaric@auburn.edu [[alternative HTML version deleted]]

Hello, The "arma" function in the "tseries" package allows estimation of models with specific "ar" and "ma" lags with its "lag" argument. For example: y[t] = a[0] + a[1]y[t-3] +b[1]e[t-2] + e[t] can be estimated with the following specification : arma(y, lag=list(ar=3,ma=2)). Is this possible with the "arima" function in the

Hello, I have just completed first experiments in using R, especially creating and using ARIMA models, e.g. # create a model as in example(arima) fit <- arima(USAccDeaths, order = c(1,1,1),seasonal = list(order=c(1,1,1))) # use the model to generate a prediction dp<-predict(fit, n.ahead = 24) plot(dp$pred) # view the prediction Now I created a combined chart of the original and

Can someone direct me to a resource or resources that list the formulae used by R functions (i.e. predict.lm ) to calculate the statistic reported. I am not a programmer and studying the r code is extremely slow going. I have searched r-project.org and all the function help files without success. For example I have attempted to replicate by hand the se.fit calculation from a lm object

I am relatively new to R and object oriented programming. I have relied on SAS for most of my data analysis. I teach an introductory undergraduate forecasting course using the Diebold text and I am considering using R in addition to SAS and Eviews in the course. I work primarily with univariate or multivariate time series data. I am having a great deal of difficulty understanding and working with

I have a data set with observations on 549 cities spanning an 18 year period. However, some of cities did not report in one or more of the 18 years. I would like to implement the procedure suggested by Wooldridge section 17.1.3 in his "Econometric analysis of cross section and panel data" to correct for attrition. For example the table below indicates that the 3rd and the 7th cities in

Hi, I am trying to understand exactly what xreg does in arima. The documentation for xreg says:"xreg Optionally, a vector or matrix of external regressors, which must have the same number of rows as x." What does this mean with regard to the action of xreg in arima? Apparently somehow xreg made the following two arima fit equivalent in R: arima(x, order=c(1,1,1), xreg=1:length(x)) is

I don't understand where is my problem. I tried the problem suggested by Prof. Brian Ripley data(USAccDeaths, package="ts") and it worked. So this is not a machine or configuration problem. This is my series (dataset1.ts) Jan Feb Mar Apr May Jun Jul Aug 1998 20957656 22280838 28048581 32286754 36456729 35575315 34127179 34363108 1999

Is anyone aware of a procedure to apply Newey-West corrections for autocorrelation to a SUR regression model? The SANDWICH package seems to be applicable only to LM or GLM models. Thanks, Richard Saba Department of Economics Auburn University Email: sabaric at auburn.edu

Hello! Given is an Excel-Sheet with actually 11,000 rows and 9 columns. I want to work with the data in R. The contents are similar to my following example. I have a list with ID-number, personal name and two kinds of loan-values. I want to aggregate the list, that for each person only one row remains and where the loan-values are added. First I tried some commands with tapply but had no

Hi I need to insert a blank row after every row in R data frame. I have achieved it through: df[rep(1:nrow(df),1,each=2),] But it inserts a row with name of previous row, while i want a complete blank row without any name/title. Please guide me Regards Saba

Hi I have two columns in data frame. First column is based on "ID" assigned to each group of my data (similar ID depicts one group). From second column, I want to identify highest value among each group and want to assign the same ID to that highest value. Right now the data looks like: ID Value 1 0.69 1 0.31 2 0.01 2 0.99 3 1.00 4 NA 4

Well, something like this would work (there may be slicker solutions): > z <- data.frame(a=1:3,b = letters[1:3]) > i <- seq_len(nrow(z)) *2 > z <-rbind(z,z) > z[i, ] <- matrix(NA, nr=nrow(z),nc=ncol(z)) > z a b 1 1 a 2 NA <NA> 3 3 c 4 NA <NA> 5 2 b 6 NA <NA> But I agree with you that there is probably a way to handle the underlying

Can someone enlighten me on why the following doesn't work? setwd('C:/Temp/R') d <- rep(1:53,2) (s <- ts(d, frequency=53, start=c(2000,10))) n <- length(s) k <- n%/%3 for(i in (n-k):n) { st <- c(start(s)[1] + (start(s)[2] + i)%/%frequency(s), (start(s)[2] + i) %% frequency(s)) ed <- c(start(s)[1] +

Hi Saba, I don't know how to do what you want and I also cannot see why. If you describe what you hope to achieve there might be a different solution. Best wishes Ulrik Saba Sehrish via R-help <r-help at r-project.org> schrieb am So., 24. Apr. 2016 14:04: > Hi > > I need to insert a blank row after every row in R data frame. I have > achieved it through: > > >

The "tsdiag" function in the TSA package overrides the "tsdiag" function in the "stats" package. There are a few annoying bugs in the TSA's version of the function so I would like to use the "stats" function but still have access to other TSA functions. I have tried using stats::tsdiag( ) but as long as the TSA package is attached the function from

Hi I have a data frame with rows specifying companies (codes are assigned to companies) and columns specify months (monthly data). The data is based on male (M) and female (F) information for each month. Following is an example of how my data looks like: 01 02 03 04 001 M M M na 001 F M M M 002 M na F F 003 F F F M 003 F F M na 003 M