similar to: Factors to Columns

Hi, I am very new to R and I've been trying to work through the R book to gain a better idea of the code (which is also completely new to me). Initially I imputed my data from a text file and that seemed to work ok, but I'm trying to examine linear relationships between gdist and gair, gdist and gsub, m6dist and m6air, etc. This didn't work and I think it might have something to do

Hello R Users, I am new to R. I have two data sets i) TOMS aerosol optical depth(AOD) and ii) TOMS ozone(O3). > > AOD data is on 1x1 grid and O3 data is on 5x5 grid. > > First I want to read AOD and O3 as it is and then I want to regrid AOD on > 5x5 grid as O3. > > Reading is first problem. > > FIRST PROBLEM READING AOD: > > AOD data is in following format: >

Dear friends, when i use glm() to fit my data, i use glm(formula = snail ~ vegtype + mhveg + humidity + elevation + soiltem, *family = Gamma(link = inverse),* data =a,)) It shows: error in eval(expr, envir, enclos) : *gamma distribution don't allow negative value*. But i use result<-glm(formula = snail ~ vegtype + mhveg + humidity + elevation + soiltem, family = poisson, data =a) #this

Dear all- I have a dataset (see a sample below - but the whole dataset is June 2005 - June 2008). The "LST" format is "YYMMDDHHmm" and I would like to get the hourly average of the "mph" for the summer months (spanning all years). I have been trying to use "aggregate" but am not having much success at all! any thoughts would be greatly appreciated.

Hi folks, I am running a very simple regression using mylm <- lm(mass ~ tarsus, na.action=na.exclude) I would like the use the residuals from this analysis for more regression but I'm running into a snag when I try cbind(mylm$residuals, mydata) # where my data is the original data set The error tells me that it cannot use cbind because the length of mylm$residuals is

# hi all, # I'm trying to plot temperatures by date in a trellis plot by their stations # I'm plotting the following data.frame library(lattice) h <- structure(list(station_name = structure(c(3L, 4L, 2L, 10L, 11L, 12L, 6L, 7L, 5L, 8L, 9L, 3L, 4L, 2L, 10L, 11L, 12L, 6L, 7L, 5L, 8L, 9L, 3L, 4L, 2L, 10L, 11L, 12L, 6L, 7L), .Label = c("Ashqelon", "Beer Sheva",

Estimada comunidad tengo un problema del que no encuentro datos que me ayuden mucho en la web. Estoy haciendo calculos por grupos con data,table. Tengo un archivo (zp.res) con tres columnas que clasifican los datos (sol, con, dia) y una columna de datos numericos (media), de la siguiente forma: sol con dia media 1: con 0 1 -22.6 2: con 0 1 -36.6 3: con 0 1 -35.6 y

Hi, Suppose I have the following vector (data points): > x [1] 36.0 57.3 73.3 92.0 300.4 80.9 19.8 31.4 85.8 44.9 24.6 48.0 [13] 28.0 38.3 85.2 103.6 154.4 128.5 38.3 72.4 122.7 123.1 41.8 21.7 [25] 143.6 120.2 46.6 29.2 44.8 25.0 57.3 96.4 29.4 62.9 66.4 30.0 [37] 24.1 14.8 56.6 102.4 117.5 90.4 37.2 79.6 27.8 17.1 26.6 16.3 [49] 41.4 48.9 24.1

The partial R-square (or coefficient of partial determination, or squared partial correlation coefficients) measures the marginal contribution of one explanatory variable when all others are already included in multiple linear regression model. The following link has very clear explanations on partial and semi-partial correlation: http://www.psy.jhu.edu/~ashelton/courses/stats315/week2.pdf In

Hello R Users, I have two data sets i) TOMS aerosol optical depth(AOD) and ii) TOMS ozone(O3). AOD data is on 1x1 grid and O3 data is on 5x5 grid. First I want to read AOD and O3 as it is and then I want to regrid AOD on 5x5 grid as O3. Reading is first problem. FIRST PROBLEM READING AOD: AOD data is in following format: ######### Latitute: 89.5 167 0 0 0 0 0 182 0 0 0 0 0 0 0 0 0 0 0 0 200

Dear R users, I am reading data from a file where there are some missing that are represented by -9999.00. I am using the command below. =====My original data =========== PARM = TMPC;T12X;T12N;DWPC;PALT;SKNT;DRCT;P24M;CLCL STN YYMMDD/HHMM TMPC T12X T12N DWPC PALT SKNT DRCT P24M CLCL 820420 110429/1200 22.50 -9999.00

Hello, Two lapply questions (system info and sample data below): 1) Why does the first form of command1 add the name of y _after_ the str() output rather than before as does the second (preferred) form? # command1 version1 invisible(lapply(ls(pattern='bn'), function(y) cat(y, "\n", str(get(y)), "\n") )) # command1 version2 (preferred output)

Dear List, I am not sure how should i optimize a log-likelihood numerically: Here is a Text book example from Statistical Inference by George Casella, 2nd Edition Casella and Berger, Roger L. Berger (2002, pp. 355, ex. 7.4 # 7.2.b): data = x = c(20.0, 23.9, 20.9, 23.8, 25.0, 24.0, 21.7, 23.8, 22.8, 23.1, 23.1, 23.5, 23.0, 23.0) n <- length(x) # likelihood from a 2 parameter Gamma(alpha,

If I'm not mistaken, partial R-squared is the R^2 of the quantities plotted in a partial residual plot, so you can base the computation on that. Prof. Fox's `car' package on CRAN has a function for creating those plots, but you need to figure out the way to extract the quantities being plotted. [In any case, the basic tools for doing such computations are all in R, and it

Estimados Al dirigir la lectura de un folder tYA1.csv me da este error y no me percato del motivo, adjunto archivo. Espero su ayuda Saludos Jos? > setwd("D:/Public/Documents/R/bioimpedancia") > a<-read.csv("tYA1.csv",header=TRUE, sep=",", dec=".") Error in read.table(file = file, header = header, sep = sep, quote = quote, : more

Dear Community, I have been using two types of survival programs to analyse a data set. The first one is an R function called aftreg. The second one an STATA function called streg. Both of them include the same analyisis with a weibull distribution. Yet, results are very different. Shouldn't the results be the same? Kind regards, J -- View this message in context:

Dear RUsers, I guess this is an easy question for someone a little familiar with programming...(which I am not)... I've got 2 colummns, one shows just dates(SST_date, Class 'Date' num), the other one shows the SeaSurfaceTemperature (SST, num) at that certain date. SST_date SST 2008-01-01 22.2 2008-01-02 21.8 2008-01-03 22.8 2008-01-04 22.9 2008-01-05 23.1 2008-01-06 23.2 ...

I'm using a very long irregular time-series of air temperature and relative humidity of this kind (this is an extract only) its.format("% Y%d%m %X) > base T H 20020601 12.00.00 27.1 47 20020601 15.00.00 29.1 39 20020601 18.00.00 27.4 39 20020601 21.00.00 24.0 40 20020602 0.00.00 22.0 73 20020602 3.00.00 19.2 49 20020602 6.00.00 19.5 74 20020602

Dear R-users, I have a dataset with categories and numbers. I would like to compute and add cumulative numbers to the dataset. I do not understand the structure of by(...) or tapply(...) output enough to handle it. Here a small example -------------- d<-expand.grid(a=1:5,b=1:3,c=1:2) d$n = 10 * d$a + d$b +0.1* d$c Sn<-by(d$n,list(d$a,d$c),cumsum) str(Sn) --------- List of 10 $ : num

hello, I'd like know how to sort a data frame in R for example how I should do to sort by Catholic with swiss data frame like below thanks Fertility Agriculture Examination Education Catholic Infant.Mortality Courtelary 80.2 17.0 15 12 9.96 22.2 Delemont 83.1 45.1 6 9 84.84 22.2