similar to: Excel Regression Function

Hallo, I am totally confused why Excel and R give me totally different regression results for the data below. If you know the solution, please enlighten me. In Excel I used LINEST() and Data>Data Analysis>Regression and both (fortunately) gave the same result. The coefficients were: /b0=1.16, b1=0.957, b2=0.024, R2=0.0027, adjusted R2=-0.017/ In R I used

Hey, I have an array with the dimensions 200x6x200 and I want to save it in a textfile. I want to be able to reload the text file to get the same array again: new.array<-load(mytextfile.txt) or something similar. I was not able to figure out a way to do that with write.table without having to save 200 text files. Is there another way? Thank you! Frauke -- View this message in context:

Dear R community, I have the following problem I hoped you could help me with. My data is save in thousand of files with a weird extension containing for numbers and a z. For example *.1405z. With list.files I managed to load this data into R. It looks like this (the row numbers are not in the original file): 35 :LATEST STAGE 3.60 FT AT 730 AM CST ON 0102 36

Hi everybody, recently a member of the community pointed me to the useful predict.lm() comment. While I was toying with it, I stumbled across the following problem. I do the regression with data from five years. But I want to do a prediction with predict.lm for only one year. Thus my dataframe for predict.lm(mod, newdata=dataframe) is shorter than the orginial vector that I did the regression

Hey everybody, it would be really appreciate if you knew the solution to the following problem. I am trying to load data from the internet into R without having to save them. However, I need to acess a different website for each dataset. So I want to alternate an element in the URL. Eventually, I want to fill a 3 dimensional matrix/array where each slice is a two-dimensional matrix from the

Sorry for any cross-posting! Hello, My name is Frauke Lehmann and I'm writing my master thesis about the social formation of free software/open source (FS/OS) developers. A questionnaire is one part of my research - besides interviews and observations. It would be really nice, if you supported my survey by filling in my questionnaire (takes 20-30 min). I understand FS/OS developers as

I'm having trouble using the read.mtp function in the foreign package to import datasets from minitab (.mtw) format. Specifically, each file I try to import fails to load any data beyond a header row stating the version of Minitab that saved the dataset. I get this error: incomplete final line found by readtableHeader on 'income.mtw' The dataset appears to be complete (ie, using

Hi I am performing an analysis of variance with two factors, each with two levels. I have differing numbers of observations in each of the four combinations, but all four combinations *are* present (2 of the factor combinations have 3 observations, 1 has 4 and 1 has 5) I have used both anova(aov(...)) and anova(lm(...)) in R and it gave the same result - as expected. I then plugged this into

Dear All, Would like to ask the inconsistency in the autocorrelation from R with SPSS/Minitab. I have tried a dataset x with 20 data (1-20) and ask R to give the autocorrelation of different lags using the command < acf(x, lag.max=100, type = "correlation"), However while SPSS and Minitab give the same answers (0.85 for lag1), R gives 0.3688 which is much smaller. Obviously, the

Dear R list, I have been trying to do a linear model, extracting the effect of a covariate.... and the results do not match, when I do it with other programs (e.g. minitab).... so it is obvious that I was doing something wrong. Whan I do it with minitab, I have this results: (sector is a factor and depth is the covariate): Source DF Seq SS Adj SS Adj MS F P

Hi, I ran a small data set from a factorial experiment through R, Minitab and JMP... the result from R is significantly different from what Minitab or JMP give... The data set is at the following link: http://www.personal.psu.edu/nug107/Uploads/2x3_16repsANOVA.txt The first 5 columns are the factors and the next three are responses. In particular, for the response beta11MSE, two of the

Hi R-help. I am trying to run a linear mixed model with nested factors with either lme or lmer and I am having no luck obtaining the same results as Minitab. Here is Minitab's code: MTB > GLM 'count' = site year replicate(site year) site*year; SUBC> Random 'year' 'replicate'; Can you tell me how to code this in R? The settings are typeII, Tukey,

Hello, Given a probability function: p(x) = 12 / (25(x+1)) , x=0, 1, 2, 3 we generate the following values: C1 C2 0 0.48 1 0.24 2 0.16 3 0.12 Now, I'm supposed to create 50 random values using this table. In MiniTab, I simply selected Calc -> Random Data -> Discrete, and selected the columns, and it created 50 random values in a new column.[1] How do I do the

A strange thing happened. After installing the most recent RC version of 2.7 (2008-04-20 r45403) I compiled it as usual with no errors. After installing it I ran "make fullcheck". I got as far as testing recommended packages and I got the following: ... -------- Testing package foreign -------- Running examples in 'foreign-Ex.R' ... Comparing `foreign-Ex.Rout' to

I recently downloaded R for Windows, running on Win XP. I'm trying to create a perspective plot but not having any luck after reading the R manual and several examples found on the Internet. I have a 100 x 100 matrix of Z data as a tab-delimited text file exported from Minitab. I read this in to R using read.delim; this seemed to go ok. I created X and Y using seq() to get 100 divisions

Does anyone else miss email-friendly character graphics such as the following example, produced using Minitab? Histogram of C6 N = 478 N* = 21 Each * represents 2 observation(s) Midpoint Count -12 16 ******** -11 53 *************************** -10 63 ******************************** -9 83

I want to specify a two-factor model in lme, which should be easy? Here's what I have: factor 1 - treatment FIXED (two levels) factor 2 - genotype RANDOM (160 genotypes in total) I need a model that tells me whether the treatment, genotype and interaction terms are significant. I have been reading 'Mixed effects models in S' but in all examples the random factor is not in the main

hi folks, Bit of a newbie, but I've spent a fair bit of time looking for an answer on this, with no joy. Can anyone help me? Dataset: A single column of values in a csv file (eg. 52, 53, 54, 85, etc) Goal: In Minitab, you have what they call a dot plot. It's a histogram, where a single dot represents a set of identical values (eg. 57, 57, 57 would be one dot). Multiple dots are

Hola, LLevo buscando desde hace tiempo como hacer el Goodness of fit test en R. Es decir, me explico, intento hacer una cosa parecida que se hace en Minitab, por ejemplo, yo tengo un conjunto de datos, y lo que quiero es sabes que tipo de distibución es, en minitab se hace un histograma para ver si se ajusta bien o no a la campana de Gauss, luego vemos si aproximar la distribución de la muestra

Dear R-Friends, Sorry to bother everyone with my earlier question: "Do we have similar R function to work like Minitab's INDICATOR?" I found the way to make things work: e.g., > x <- c(2,2,5,3,6,5,NA) > model.matrix(~ factor(x) - 1) factor(x)2 factor(x)3 factor(x)5 factor(x)6 1 1 0 0 0 2 1 0 0 0