search for: loblolly

...o R and have tried to figure out how to automate this process instead of using excel. I have read in this dataframe into r with read.table. I need to reshape the data from the first table into the format of the second table. TractID StandID Species CruiseDate DBHClass TreesPerAcre Carbon Stand 1 Loblolly Pine 5/20/2010 10 1.2 Carbon Stand 1 Loblolly Pine 5/20/2010 12 1.2 Carbon Stand 1 Loblolly Pine 5/20/2010 14 0.61 Carbon Stand 1 Loblolly Pine 5/20/2010 16 0.75 Carbon Stand 1 Hard Hardwoods 5/20/2010 6 27.4 Carbon Stand 1 Hard Hardwoods 5/20/201...

Hallo! I want to plot multiple grouped data in a postscript file using a loop. As I use a loop no plot (or just one empty plot) is generated. Here an example: library(nlme) data(Loblolly) # example data from nlme postscript("PSFile.ps") for (i in 1:1) # just as example { plot(Loblolly) } dev.off() Result: Just an empty PSFile.ps. (Withoput the loop it works. May anybody help? Karl __________________________________________________________________

...o be able to find answer so I am hoping someone here can help. I found that if the factor names are all in numbers, fitting the model in lm would return labels that are not very recognizable. # Example: let's just assume that we want to fit this model fit <- lm(height ~ age + Seed, data=Loblolly) # See the category names are all mangled up here fit Call: lm(formula = height ~ age + Seed, data = Loblolly) Coefficients: (Intercept) age Seed.L Seed.Q Seed.C Seed^4 -1.31240 2.59052 4.86941 0.87307 0.37894 -0.46853 Seed^...

...on Akaike's AIC. The AIC values I get for exactly the same model formulation --for example a linear model with no random effects fit with gls and lm, respectively-- do not fit, although the values of the four model parameters are exactly the same. For example: m1 <- gls(height ~ age, data = Loblolly) m2 <- lm(height ~ age, data = Loblolly) m1$coefficients (Intercept) age -1.312396 2.590523 m2$coefficients (Intercept) age -1.312396 2.590523 But then: AIC(m1) [1] 428.9243 AIC(m2) [1] 423.9153 I am trying to compare between more complex models, i.e. different ways...

I ran into a problem trying to make a plot from a file that's read using source. Basically, I have the following code in a file "plot.R" : library(nlme) data(Loblolly) fm1 <- nlme(height ~ SSasymp(age, Asym, R0, lrc), data = Loblolly, fixed = Asym + R0 + lrc ~ 1, random = Asym ~ 1, start = c(Asym = 103, R0 = -8.5, lrc = -3.3)) windows(6,6) plot(fm1) This code is taken from the help page for 'nlme'. If...

Hello, How do I specify the formula and random effects without a startup object ? I thought it would be a mixture of nls and lme. after trying very hard, I ask for help on using nlme. Can someone hint me to some examples? I constructed a try using the example from nls: #variables are density, conc and Run #all works fine with nls DNase1 <- subset(DNase, Run == 1 ) fm2DNase1 <- nls(

I have a need to call and pass arguments to nlme() from within another function. I use R version 1.8. I have found an apparent way to make this work, but I would appreciate some comments on whether this fix is really appropriate, or there is another way to do it that does not involve changing the source code. I don't have enough experience to start changing the sorurce code of a library

...ation, but for purposes of this illustrative example, the parameters are fine. The result should be a list of the nlme object and 'OK' (which should be 5 for the example). I'm using R version 1.9.1 on Windows XP. Thanks for any thoughts, Ken ################ library(nlme) data(Loblolly) maxIter <- c(1, 1, 1, 1, 1) returnObject <- c(FALSE, FALSE, FALSE, FALSE, TRUE) nlsList.Object <- nlsList(SSasymp, Loblolly) M1 <- function(maxIter, returnObject) { ok <- FALSE OK <- 0 while(ok==FALSE) { OK <- OK + 1 nlme.control.parms <- list...

...problema con xtable y nlme, tomando un ejemplo del manual de nlme para obtener los resultados en latex utilizando xtable, se puede utilizar el siguiente código, pero hay un problema y causa error. library(nlme) library(xtable) fm1 <- nlme(height ~ SSasymp(age, Asym, R0, lrc), data = Loblolly, fixed = Asym + R0 + lrc ~ 1, random = Asym ~ 1, start = c(Asym = 103, R0 = -8.5, lrc = -3.3)) summary(fm1) xtable(summary(fm1)) Por si prefieren no ejecutar el código, el mensaje de error es: Error en UseMethod("xtable") : no applicable method for...

...dometh Pharmacokinetics of Indomethicin InsectSprays Effectiveness of Insect Sprays JohnsonJohnson Quarterly Earnings per Johnson & Johnson Share LakeHuron Level of Lake Huron 1875-1972 LifeCycleSavings Intercountry Life-Cycle Savings Data Loblolly Growth of Loblolly pine trees Nile Flow of the River Nile Orange Growth of orange trees OrchardSprays Potency of Orchard Sprays PlantGrowth Results from an Experiment on Plant Growth Puromycin Reaction velocity o...

...1 6 71 60.92 25 301 7 2 4.55 3 303 8 16 10.92 5 303 9 30 29.07 10 303 10 44 42.83 15 303 11 58 53.88 20 303 12 72 63.39 25 303 13 3 4.79 3 305 14 17 11.37 5 305 15 31 30.21 10 305 16 45 44.40 15 305 17 59 55.82 20 305 18 73 64.10 25 305 ----- (the loblolly data) into this form: ---- 3 5 10 15 20 25 301 4.51 10.89 28.72 41.74 52.70 60.92 303 4.55 10.92 29.07 42.83 53.88 63.39 305 4.79 11.37 30.21 44.40 55.82 64.10 --- the columns contain the height for each age level and the row the seed level right now im doing it like this...

Dear all I try to refine my nlme models and with partial success. The model is refined and fitted (using Pinheiro/Bates book as a tutorial) but when I try to plot plot(augPred(fit4)) I obtain Error in predict.nlme(object, value[1:(nrow(value)/nL), , drop = FALSE], : Levels (0,3.5],(3.5,5],(5,7],(7,Inf] not allowed for vykon.fac > Is it due to the fact that I have unbalanced

...with-blas or --with-lapack as the manuals indicated; the box does have its copy of blas.so and lapack.so under /usr/lib) 5. my test of lapack in R is to run: library(nlme); and then run the example from this package: fm1 <- nlme(height ~ SSasymp(age, Asym, R0, lrc), data = Loblolly, fixed = Asym + R0 + lrc ~ 1, random = Asym ~ 1, start = c(Asym = 103, R0 = -8.5, lrc = -3.3)) 6. here is the error: + + + + Error in chol.default((value + t(value))/2) : lapack routines cannot be loaded In addition: Warning message: In chol.de...

...frset' not found so it seems to me this must affect all packages in Debian sid that were built before the release of R 3.4.0! And in fact, nlme, is affected as well: > library(nlme) > example(nlme) nlme> fm1 <- nlme(height ~ SSasymp(age, Asym, R0, lrc), nlme+ data = Loblolly, nlme+ fixed = Asym + R0 + lrc ~ 1, nlme+ random = Asym ~ 1, nlme+ start = c(Asym = 103, R0 = -8.5, lrc = -3.3)) Error in pdFactor.pdLogChol(X[[i]], ...) : object 'logChol_pd' not found So before I start spamming the Debian BTS, what would be the right w...

Dear list members, I am working with a multilevel growth curve, that in its simplest form goes like follows: Yit = Ai + Bi t + eit (the error term is assumed to follow an AR(1) autorregressive process) One major topic in my research is the convergence in the values of Y over time. Thus, I am interested in the relationship between the random effects for the intercept and the slope, and I

Am Dienstag, 25. April 2017, 08:50:34 schrieb Dirk Eddelbuettel: > On 25 April 2017 at 14:58, G?ran Brostr?m wrote: > | hello, > | > | I just installed R-3.4.0 from scratch: > | > | $ sudo apt install r-base > | > | but when I try > | > | > library(survival, lib.loc = "/usr/lib/R/library") > | > fit <- coxph(Surv(exit, event) ~ x, data =

...s it has integer (and not say double) codes. o structure() ensures that objects with added class "factor" have integer codes. o The "formula" and "outer" attributes of datasets 'ChickWeight', 'CO2', 'DNase', 'Indometh', 'Loblolly', 'Orange' and 'Theoph' now have an empty environment and not the environment used to dump the datasets in the package. o Dataset 'Seatbelts' now correctly has class c("mts", "ts"). o str() now labels classes on data frames more coherently...

...s it has integer (and not say double) codes. o structure() ensures that objects with added class "factor" have integer codes. o The "formula" and "outer" attributes of datasets 'ChickWeight', 'CO2', 'DNase', 'Indometh', 'Loblolly', 'Orange' and 'Theoph' now have an empty environment and not the environment used to dump the datasets in the package. o Dataset 'Seatbelts' now correctly has class c("mts", "ts"). o str() now labels classes on data frames more coherently...

...html latex example CO2 text html latex example ChickWeight text html latex example DNase text html latex example Indometh text html latex example Loblolly text html latex example NLSstAsymptotic text html latex example NLSstClosestX text html latex example NLSstLfAsymptote text html latex example NLSstRtAsymptote te...

...library/nls/data/CO2.R action: create D: file: /usr/local/lib/R/library/nls/data/ChickWeight.R action: create D: file: /usr/local/lib/R/library/nls/data/DNase.R action: create D: file: /usr/local/lib/R/library/nls/data/Indometh.R action: create D: file: /usr/local/lib/R/library/nls/data/Loblolly.R action: create D: file: /usr/local/lib/R/library/nls/data/Orange.R action: create D: file: /usr/local/lib/R/library/nls/data/Orthodont.R action: create D: file: /usr/local/lib/R/library/nls/data/Pixel.R action: create D: file: /usr/local/lib/R/library/nls/data/Puromycin.R action: crea...