similar to: Multiple factorial comparison LSD

LSD-test produces error for this code; code <- as.factor(Rotationdata_R$`Rot/code`) #factor in the main Nitrogen <- as.factor(Rotationdata_R$Nitrogen) #factor in the sub Rep <- as.factor(Rotationdata_R$REP) #blocks Year <- as.factor(Rotationdata_R$YEAR) #years model <- aov(Rotationdata_R$`GY(Mg/ha)`~Rep+code*as.factor(Nitrogen)+Error(Rep/Year/code),data=Rotationdata_R)

> On Dec 25, 2017, at 2:09 PM, Ahmed Attia <ahmedatia80 at gmail.com> wrote: > > The model should be class aov or lm and my model class is aovlist. > tried tidy from broom library but did not work. To make it class aov, > I had to remove the error term; > > model <- aov(Rotationdata_R$`GY(Mg/ha)`~Rep+code*as.factor(Nitrogen),data=Rotationdata_R) You seemed to have

> On Dec 25, 2017, at 10:21 AM, Ahmed Attia <ahmedatia80 at gmail.com> wrote: > > LSD.test ?LSD.test No documentation for ?LSD.test? in specified packages and libraries: you could try ???LSD.test? -- David Winsemius Alameda, CA, USA 'Any technology distinguishable from magic is insufficiently advanced.' -Gehm's Corollary to Clarke's Third Law

The model should be class aov or lm and my model class is aovlist. tried tidy from broom library but did not work. To make it class aov, I had to remove the error term; model <- aov(Rotationdata_R$`GY(Mg/ha)`~Rep+code*as.factor(Nitrogen),data=Rotationdata_R) Ahmed Attia, Ph.D. Agronomist & Soil Scientist On Mon, Dec 25, 2017 at 7:38 PM, David Winsemius <dwinsemius at

Hi there, I am trying to run LSD.test(model) I used the following commands: attach(model) m1<- glm(ttl.m ~ site+year, family=quasipoisson, data= model) df<-df.residual(m1) MSerror<-deviance(m1)/df The following command did not work: comparison<- LSD.test (ttl.m, site+year, df, MSerror, alpha = 0.05, group=FALSE) I get an error message: Error: could not find function

Hi there, ============================= x=c(145,40,40,120,180, 140,155,90,160,95, 195,150,205,110,160, 45,40,195,65,145, 195,230,115,235,225, 120,55,50,80,45 ) y2=c( rep(as.character(1),5), rep(as.character(2),5), rep(as.character(3),5), rep(as.character(4),5), rep(as.character(5),5), rep(as.character(6),5) ) crd2=data.frame(x,y2) model1=aov(x~y2,data=crd2) TukeyHSD(model1)

Hi there, Is there a function that can do a Fisher's LSD multiple comparisons in a two-way ANOVA? I hope to get a result similar with TukeyHSD(). Especially, I hope to know the significance of comparisons between the interactions of two factors. In the following example: x <- c(76, 84, 78, 80, 82, 70, 62, 72, 71, 69, 72, 74, 66, 74, 68, 66, 69, 72, 72, 78, 74, 71, 73, 67, 86, 67, 72,

I am returning this to the R-help list. Please keep followups on the list. Yes, it can be done. It is not currently easy because multcomp doesn't have the syntax yet. Making this easy is on Torsten's to-do list for the multcomp package. See the MMC.WoodEnergy example in the HH package. The current version on CRAN is HH_1.17. Please see the discussion of this example in R-help:

Hola de nuevo R-Users, me he dejado cosas para aclara. Primero de todo tengo cinco repeticiones y 20 missings, así que mi n es de 5×10×3×5-20= 730 datos en total, todos los grupos tienen al menos 3 representantes. Segundo: Las variables estudiadas son Producción neta, Peso de 100 semillas y Proteína. Tercero: Observo los mismos genotipos (G) en varios años (A) en las misma localidades

Hi, I'm designing a experiment in order to compare the growing of several clones of a tree specie. It will be a complete randomized block design. How can I decide what model of mean comparision to choose? LSD, HSD,TukeyHSD, Duncan,...? Thanks in advance

Queridos R-users: Tengo una duda que hace mucho tiempo que estoy intentando resolver, os explico a modo de ejemplo: Tengo estos efectos: Año(5 niveles),Localidad (10 niveles) y genotipo (3 niveles), año y localidad son aleatorios y genotipo es fijo (los he escogido yo). Me gustaría hacer obtener una tabla parecida a la Tabla Anova donde aparezca cada factor y sus interacciones y

Hi all, I want to apologise first for being a beginner with linux/emacs/ess; I am pretty good with R ;). I have R-1.9.1 installed on my directory of a linux server, I also have ess 5.2.8 installed there as well. When I call R using (C-u M-x R) in emacs, i receive the following error [no match]. I was wondering if emacs is not looking for ess in the right place (if there is something i have to

Hello, I want to fit some non linear models with the Levenberg-Marquardt algorithm. It doesn''t seem to exist any function to do this in R ( well, maybe one does, but I''m a new user, and the only documentation I have is "An introduction to R"). I''d like to know if this function exists, maybe throught an additionnal package. I''d also like to know if if

Dear R users, I have used the following model: M1 <- gls(Nblad ~ Concentration+Season + Concentration:Season, data=DDD, weights=varIdent(form=~ 1 | Season*Concentration)) to assess the effect of Concentration and Season on nitrogen uptake by leaves (Nblad). I accounted for the difference in variance across the factor levels by using the varIdent function. Then I wanted to perform multiple

Hi, I want to sample from a distribution (say a normal distribution, for example) using vectors of the different parameters (i.e. the mean and standard deviation). That is, I have a list/vector of say 100 means and another of the corresponding 100 SD's, and I want a matrix of 100 rows (one for each mean and SD pair) each having 1000 random samples. Something like: sample_matrix =

There are two unexpected failures in the check-all (this check-all runs with self-build-clang): Failing Tests (2): Clang Tools :: clang-tidy/clang-tidy-diff.cpp Clang Tools :: clang-tidy/file-filter.cpp Last log: http://lab.llvm.org:8011/builders/clang-x64-ninja-win7/builds/340/steps/ninja%20check%202/logs/stdio From: Yaron Keren [mailto:yaron.keren at gmail.com] Sent: Thursday, April

Hola a todos estoy aplicando la función polinómica de Hossfeld [1], y algunos otros modelos no lineales para tratar de ajustarlos a un grupo de datos forestales,   [1] Y= b*t*exp(c)/(t*exp(c)+a) Al colocar la función en R con parámetros estimados, me devuelve los siguiente: ## model1 <- nls(ho ~ (b*edad*exp(c)/(edad*exp(c)+a)), data=nigra,     start=list(a=0.005,b=0.08,c=-0.00006),

I agree, it is great. I have some regression tests (check-all) failures on Windows locally. Does the buildbot show the same? On Thu, Apr 23, 2015 at 11:16 AM Yaron Keren <yaron.keren at gmail.com> wrote: > That's great to hear! > > 2015-04-23 12:08 GMT+03:00 Fedorova, Vera <vera.fedorova at intel.com>: > >> Hi All, >> >> >> >> This is

Hi All, This is to let you know that a new buildbot for Windows native LLVM/Clang testing is established: http://lab.llvm.org:8011/builders/clang-x64-ninja-win7 . Hardware + OS configuration is: Haswell desktop with Windows 7 + Visual Studio 2013 Update 4. It is hosted by Intel and hopefully will contribute to improve quality of the LLVM/Clang on Windows being developed in the LLVM community.

2015-05-03 21:02 GMT+09:00 Yaron Keren <yaron.keren at gmail.com>: > I now tried the extra tests and get the same failures: > > Clang Tools :: clang-tidy/clang-tidy-diff.cpp > Clang Tools :: clang-tidy/file-filter.cpp > > Takumi, I see you added requires:shell in r211831 and r220837. > > When using MSYS requires:shell is true but test fail, is it OK to >