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Hi, 1. How do I construct 95% prediction interval for new x values, for example - x = 30000? 2. How do I construct 95% confidence interval? my dataframe is as follows : >dt structure(list(y = c(26100000, 60500000, 16200000, 30700000, 70100000, 57700000, 46700000, 8600000, 10000000, 61800000, 30200000, 52200000, 71900000, 55000000, 12700000 ), x = c(108000, 136000,

Hi, I would like to estimate something like y = a + b*d2*y + c*d3*y where the dummies are created from some vector d with three (actually many more) levels using factor(). But either there is included the variable y or d1*y. How could I get rid of these? Example: x = c(1,2,3,4,5,6,7,8) y = c(3,6,2,8,7,6,2,4) d = c(1,1,1,2,3,2,3,3) fd = factor(d) lm(x ~ fd*y) gives: Coefficients: (Intercept)

thank you for your answer i checked my code and it now works One more question... do you know how to have an 3D histogramm from a known matrix of probabilities Cline >From: "David Barron" <mothsailor at googlemail.com> >To: "C?line Henzelin" <celine_appui at hotmail.com>, r-help ><r-help at stat.math.ethz.ch> >Subject: Re: [R] (no subject) >Date: Sat, 18 Nov 2006 15:20:38 +0000 > >I'm not sure what the last line is trying to achieve, but this migh...

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Dear all R users, Suppose I have a VECTOR of time series y[t] consists of 2000 data point. For example suppose I have data frame which has two columns. First column represents a time series of exchange rate for 2000 days. And the second column represents the price of a commodity for the same period. Now I want to fit a OLS regression like that, y[t] = a + b*delta[y[t-1]] + c*delta[y[t-2]] +

Dear all, I am new to R. I wish to use R's multiple imputation to deal with missing data. I have a data set with the size around 300 observations and 150 variables. I checked the help function in R and could not locate how to write the codes for this. can anyone give a hand? Do appreciate your time and kindness! Q. [[alternative HTML version deleted]]

Hi I have used a polycor package for categorical correlation coefficients. I run the following script. But there were no results. Could you tell me how to correct the script? Thanks in advance, vars <- names(sdi) for (i in 1:length(vars)) { for (j in 1:length(vars)) { paste(vars[i]," and ", vars[j]) polychor(vars[i], vars[j]) # corr } } -- Kum-Hoe Hwang, Ph.D.Phone :

Hi, I have Forecast Class and Observed Class in a data matrix as below. > Sample1 FCT OBS 1 1 5 2 2 4 3 3- 3+ 4 3 3 5 3+ 3- 6 4 2 7 5 1 I want to find the difference between Observed and Forecast Classes. How can I get this done? I tried to following to convert the 1 through 5 classes, to 1 through 7 for both OBS and FCT column. > Sample1$OBS2 <- Sample1$OBS

Dear R helpers, I am trying to read a CSV file in R called EUROPE (originally an Excel file which I have saved as a CSV file) using the command EUROPEDATA <- read.csv("EUROPE.csv") EUROPE.csv is basically a matrix of dimension 440*44, and has a line of headers, i.e. each column has a name. Using read.csv I can't load the data into R properly. Although the first 20 columns or

...t; Baltimore VA Medical Center 10 North Greene Street GRECC (BT/18/GR) > Baltimore, MD 21201-1524 > > (Phone) 410-605-7119 > (Fax) 410-605-7913 (Please call phone number above prior to faxing) > jsorkin at grecc.umaryland.edu > > >>>> "David Barron" <mothsailor at googlemail.com> 08/23/07 5:38 AM >>> >>>> > A number of alternatives, such as: > > lm(y ~ 0 + x) > lm(y ~ x -1) > > See ?formula > > On 8/23/07, Michal Kneifl <xkneifl at mendelu.cz> wrote: > >> Please could anyone help m...

Hello, I wanted to create a histogram, but somehow I got stuck... The interval limits are: x = 1, 2, 3, 3.5, 4.5, 5, 5.5 The interval widths are therefore: 1, 1, 0.5, 1, 0.5, 0.5 Nothing I tried worked... Can anyone help me please? Thanks Tobias -- View this message in context: http://www.nabble.com/Histogram-tf4315900.html#a12288850 Sent from the R help mailing list archive at Nabble.com.