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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

Hi, There has been some recent work to improve the speed of the Message Authentication Codes (MACs) that are used in OpenSSH. The first improvement is a change from Markus Friedl to reuse the MAC context, rather than reinitialising it for every packet. This saves two calls to the underlying hash function (e.g. SHA1) for each packet. My tests found that this yielded at 12-16% speedup for bulk

Hi all - I am NEW to R and NEW to any type of programming. I am making heatmaps using the heatmap.2 function within gplots package. At present, when the heatmap is plotted it uses the row identifiers as 1,2,3,4...etc. However, I much rather use my own labels. I was told my another well-versed R programmer to use the follow script: x<-as.matrix(test1[,-1]) ## skip column 1 rownames(x)<-

Hola: ¿Existe alguna forma de obtener el valor numérico de los intervalos de confianza en una autocorrelación? O, por el contrario, ¿tengo que calcularlos «a mano»? (Llevo ya un rato buscando y nada.) Gracias por adelantado. Salud y Revolución. Lobo. -- Libertad es poder elegir en cualquier momento. Ahora yo elijo GNU/Linux, para no atar mis manos con las cadenas del soft propietario.

Hi. I'm using lmer() from the lme4 package (version 0.8-3) and I can't get anova() to group variables properly. I'm fitting the mixed model Response ~ Weight + Experimenter + (1|SUBJECT.NAME) + (1|Date.StudyDay) where Weight is numeric and Experimenter is a factor, ie, > str(data.df) `data.frame': 4266 obs. of 5 variables: $ SUBJECT.NAME : Factor w/ 2133 levels

CentOS Errata and Security Advisory 2005:165 https://rhn.redhat.com/errata/RHSA-2005-165.html The following updated files have been uploaded and are currently syncing to the mirrors: i386: rsh-0.17-25.3.i386.rpm rsh-server-0.17-25.3.i386.rpm src: rsh-0.17-25.3.src.rpm -------------- next part -------------- A non-text attachment was scrubbed... Name: not available Type:

CentOS Errata and Security Advisory 2005:165 https://rhn.redhat.com/errata/RHSA-2005-165.html The following updated files have been uploaded and are currently syncing to the mirrors: x86_64: rsh-0.17-25.3.x86_64.rpm rsh-server-0.17-25.3.x86_64.rpm src: rsh-0.17-25.3.src.rpm -------------- next part -------------- A non-text attachment was scrubbed... Name: not available Type:

Hello again, It appears that get_all_vars() incorrectly handles model formulae that use a right-hand side (rhs) matrix. For example, consider these two substantively identical models: # model using named variables mpg <- mtcars$mpg wt <- mtcars$wt hp <- mtcars$hp m1 <- lm(mpg ~ wt + hp) # model using matrix y <- mtcars$mpg x <- cbind(mtcars$wt, mtcars$hp) m2 <- lm(y ~ x)

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: >

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Hello everyone, I use Bob Muenchen's approach for reading in "in-stream" (to use SAS parlance) delimited data within a script. This works great: mystring <- "id,workshop,gender,q1,q2,q3,q4 1,1,f,1,1,5,1 2,2,f,2,1,4,1 3,1,f,2,2,4,3 4,2, ,3,1, ,3 5,1,m,4,5,2,4 6,2,m,5,4,5,5 7,1,m,5,3,4,4 8,2,m,4,5,5,5" mydata <- read.table( textConnection(mystring),

Hi, Being a R-newbie I am wondering how to calculate a correlation coefficient (preferably with an associated p-value) for data like: > d[,1] [1] 25.5 25.3 25.1 NA 23.3 21.5 23.8 23.2 24.2 22.7 27.6 24.2 ... > d[,2] [1] 0.0 11.1 0.0 NA 0.0 10.1 10.6 9.5 0.0 57.9 0.0 0.0 ... Apparently corr(d) from the boot-library fails with NAs in the data, also cor.test cannot cope with a

Hello, It's an alternative to use SAS by function in R? I want to plot d histograms by plot.from example bellow: Thank you! plot d 1 1 16.3 2 1 25.0 3 1 57.8 4 1 17.0 5 2 10.8 13 2 96.4 17 3 76.0 18 3 32.0 19 3 11.0 20 3 11.0 24 3 106.0 25 3 12.5 21 4 19.3 22 4 12.0 26 4 15.0 27 5 99.3 32 7 11.0 36

Hi, I''ve got the following resource: host { "host.domain.com": alias => [ "host", "alias" ], ip => "1.2.3.4", ensure => present, } The resulting line in my /etc/hosts file is: 1.2.3.4 host.domain.com Any alias definitions seem to be ignored? What am I doing wrong? Best regards, Dieter -- You received this message because

Hi all, My setup is Debian testing dom0/domUs with a 2.6.32 pvops kernel from Debian unstable. Hypervisor is 3.4.2 from Debian testing. I use network- and vif- route with a default route in domU pointing to the nic because multiple IPs with bridge would trigger port shutdown on the switch (only one mac-address allowed per port). A subnet is routed to the dom0, which then knows which addresses the

Dear all, I have this set of data. I would like to sum the EnergykWh according date sequences. > head(dt1,20) StationName date time EnergykWh 1 PALO ALTO CA / CAMBRIDGE #1 1/14/2016 12:09 4.680496 2 PALO ALTO CA / CAMBRIDGE #1 1/14/2016 19:50 6.272414 3 PALO ALTO CA / CAMBRIDGE #1 1/14/2016 20:22 1.032782 4 PALO ALTO CA / CAMBRIDGE #1 1/15/2016 8:25 11.004884 5

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

CentOS Errata and Security Advisory 2005:165 https://rhn.redhat.com/errata/RHSA-2005-165.html The following updated files have been uploaded and are currently syncing to the mirrors: files: updates/ia64/RPMS/rsh-0.17-25.3.ia64.rpm updates/ia64/RPMS/rsh-server-0.17-25.3.ia64.rpm -- Pasi Pirhonen - upi@iki.fi - http://iki.fi/upi/ -------------- next part -------------- A non-text attachment was

library(glmpath) data(heart.data) # heart.data is a list, $y a vector, $x a matrix data <- data.frame(x=I(heart.data$x), y = heart.data$y) > data[1:2,] x.1 x.2 x.3 x.4 x.5 x.6 x.7 x.8 x.9 y 1 160 12 5.73 23.11 1 49 25.3 97.2 52 1 2 144 0.01 4.41 28.61 0 55 28.87 2.06 63 1 > dimnames(heart.data$x)[[2]] [1] "sbp"

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