Displaying 5 results from an estimated 5 matches for "psme".
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pse
2017 Nov 27
0
How to extract coefficients from sequential (type 1) ANOVAs using lmer and lme
...evecoefficients are wrong. Specifically, it looks like that the coefficients arefrom ANOVA with ?marginal? (type III sums of squares). I have tried both lme (nlmepackage) and lmer (lme4 + lmerTEST packages). Examples of the results arebelow:
?
?
> #mixed-effect modelusing lme
>model.short.psme.bulk.d13c.3 <- lme(isotopebulk_add_log ~narea+sampleheight, random= ~1|tree,
+??????????????????????????? data =ht_data_short_psme, na.action = na.exclude)
>
?
>anova(model.short.psme.bulk.d13c.3, type ="sequential")
???????????? numDF denDF?? F-value p-value
(Intercept)?...
2017 Dec 07
2
parallel computing with foreach()
...code without reproducible
example.
In short, each R environment will draw a set of separate files, perform the
analysis and dump in separate folders.
splist <- c("juoc", "juos", "jusc", "pico", "pifl", "pipo", "pire", "psme")
covset <- c("PEN", "Thorn")
foreach(i = 1:length(splist)) %:%
foreach(j = 1:length(covset)) %dopar% {
spname <- splist[i]; spname
myTorP <- covset[j]; myTorP
DataSpecies = data.frame(prsabs = rep(1, 10), lon = rep(30, 10), lat =
rep(80, 10))
myResp = as.numeri...
2011 Feb 25
4
means, SD's and tapply
...0.4684844193 0.0063739377
CONU JUCA JUOC LIDE
PIAL PICO PIJE
0.0017705382 0.0003541076 0.0959631728 0.0138101983 0.3905807365
1.5651558074 0.2315864023
PILA PIMO PIMO2 PIPO
PISA POTR PSME
0.1774079320 0.1880311615 0.0311614731 0.6735127479 0.0237252125
0.0506373938 0.2000708215
QUCH QUDO QUDU QUKE
QULO QUWI Salix
0.0474504249 0.1203966006 0.0000000000 0.2071529745 0.0003541076
0.0548866856 0.0003541076
SEGI...
2006 Sep 20
1
problem coercing truncated character vector to levels
Dear R wizes,
I have a data.frame of species abundances with column names consisting
of 4 letter codes then an underscore and a number like this:
abco_1, abco_2, abco_3, psm_1, psme_2, psme_3, etc.
I would like to get an identifier for all the abco, and psme and other
species etc.
I used
spec.fact<-substring(names(spec.count),1,4)
To make a vector of the first 4 letters of each name. I tried using
spec.groups <- unique(spec.fact)
and then matc...
2017 Dec 07
0
parallel computing with foreach()
...gt; example.
>
> In short, each R environment will draw a set of separate files, perform the
> analysis and dump in separate folders.
>
> splist <- c("juoc", "juos", "jusc", "pico", "pifl", "pipo", "pire", "psme")
> covset <- c("PEN", "Thorn")
>
> foreach(i = 1:length(splist)) %:%
> foreach(j = 1:length(covset)) %dopar% {
>
> spname <- splist[i]; spname
> myTorP <- covset[j]; myTorP
>
> DataSpecies = data.frame(prsabs = rep(1, 10), lon = rep(30,...