search for: seasoning

Hi all, I am trying to interparete the result of the following output from lm; fit1 =lm(Feed _Intake ~ weight + season + weight*season) Season has three classes(x,y,z) Reults are Estimate (Intercept) 21.51559 weight 2.13051 factor(season)y 10.59739 factor(season)z 1.30421 weight:factor(season)y

Does anybody knows how to make the game run? It installs just fine, but won't run. I have been searching all over the web to find a solution, but not haven't found a single webpage or thread about it?

On Thu, May 03, 2018 at 01:09:30AM -0400, Kevin Korb via rsync wrote: > --delete only works when you sync a dir not individual files. So... > rsync -vai --delete --include='g*' --include='G*' --exclude='*' > /share/Public/videos/ /share/Backup-HDD-03 That kinda didn't work: rsync -vai --delete --include='S[A-Z]*' --include='S[a-h]*'

Hi Irucka, No problem. I guess this could be done using: Sample data: Dailydo<- structure(list(Date = structure(c(11231, 11232, 11233, 11234, 11235, 11236, 11207, 11208, 11209, 11179, 11180, 11181, 11151, 11152, 11123, 11093, 11064, 11065, 11035, 11036, 11008, 11009, 10979, 10980, 11347, 11348, 11380, 11381, 11410, 11406, 11438, 11439, 11470, 11502, 11528, 11560, 11561, 11593, 11594,

Hello R People: When using the arima function with the seasonal option, are the seasonal options only good for monthly and quarterly data, please? Also, I believe that weekly and daily data are not appropriate for seasonal parm estimation via arima. Is that correct, please? Thanks, Sincerely, Laura Holt mailto: lauraholt_983 at hotmail.com download!

Hello everybody, I need to calculate seasonal means with temperature data for my work. I have 70 files coming from weather stations, which looks like this for example: startdate <- as.POSIXct("01/01/2006", format = "%d/%m/%Y") enddate <- as.POSIXct("05/01/2006", format = "%d/%m/%Y") date <- seq(from = startdate, to = enddate, by =

Note that these are working because S* and s* are being applied to all the dirs and files within dirs. So if you had x/Something it wouldn't get copied and if you had S/else it wouldn't get copied. Maybe you want to add --prune-empty-dirs and an --include='*/' so that rsync will look inside of all dirs for matching files. On 05/03/2018 02:50 PM, Mike Brown via rsync wrote: >

> It might clarify your thinking to note that a seasonal ARIMA model > is just an ``ordinary'' ARIMA model with some coefficients > constrained to be 0 in an efficient way. E.g. a seasonal AR(1) s = > 4 model is the same as an ordinary (nonseasonal) AR(4) model with > coefficients theta_1, theta_2, and theta_3 constrained to be 0. You > can get the same answer as from

Hi all I can't find what I am looking for so I am asking here. I have a dataset that looks something like this. Year season percent_below 2000 Winter 6.9179870 2000 Spring 1.6829436 2000 Summer 1.8463501 2000 Autumn 3.8184993 2001 Winter 2.8832806 2001 Spring 2.5870511 2001 Summer 0.0000000 2001 Autumn 4.7248240 2002 Winter

Hi, I was wondering if someone could please help me. I am doing a logistic regression to compare size at maturity between 3 seasons. My model is: fit <- glm(Mature ~ Season * Size - 1, family = binomial, data=dat) where Mature is a binary response, 0 for immature, 1 for mature. There are 3 Seasons. The Season * Size interaction is significant. I would like to compare the size at 50%

Hi, I was hoping to get some advice regarding the testing of interactions, when one factor is modelled as a random effect... I have a model with binomial error structure where the response variable is the proportion of time spent at the main sett (animals were tracked for 28 consecutive days in each season, and were recorded either at the main sett or an outlier sett, so the response variable is

Hi, I am trying to assign "Season" values to dates depending on when they occur. For example, the following dates would be assigned the following "Season" numbers based on the "season" intervals detailed below in the code: ddate Season 29/12/1998 20:00:33 1 02/01/1999 05:20:44 2 02/01/1999 06:18:36 2 02/02/1999

Folks, I have been using the VAR {vars} program to find a fit for the following bi-variate time series (subset): bivariateTS<-structure(c(0.950415958293559, 0.96077848972081, 0.964348957109053, 0.967852884998915, 0.967773510751625, 0.970342843688257, 0.97613937178359, 0.980118627997436, 0.987059493773907, 0.99536830931504, 1.00622672085718, 1.01198013845981, 1.01866618122606,

rsync version 3.1.2 protocol version 31 I've run into an issue using rsync on my QNAP NAS. I've installed Entware-ng on the NAS so that I can install better versions of programs, rsync being one of them. But, I've run into an issue wqith using the --delete option, as it has problems using wildcards. Initially a backup script looked like: #!/bin/sh for d in

Hello all, I cannot seem to figure out this seemingly simple procedure. I want to sort a data frame by a specified character vector. So for : df.. <- data.frame(Season=rep(c("Summer","Fall","Winter","Spring"),4),Obs= runif(length(rep(c("Summer","Fall","Winter","Spring"),4)))) I want to sort the data frame

Thanks a lot to everybody that helped me out with this. Conclusions: (1) In order to edit arima in R: >fix(arima) or alternatively: >arima<-edit(arima) (2) This is not contained in the "Introduction to R" manual. (3) A "productive" fix of arima is attached (arma coefficients printed out and error catched so that it doesn't halt parent loops to search for

Dear R list, I have a sequence of weekly observations of number of adults and larvae in various size classes from a butterfly population living in a subtropical area with pronounced wet and dry seasons. Wet and dry seasons are each defined 26 weeks long with fixed start and end dates. The data span 103 weeks (two seasons each of wet and dry) with some missing weeks. What I would like to do is

Dear All, I am trying to fit a structural time series model using the StructTS function (package stats) with only 2 seasons (summer and winter). More than 2 seasons work fine but with 2 seasons I get this error: > fit <- StructTS(y.ts, type="BSM") Error in T[cbind(ind + 1L, ind)] <- 1 : subscript out of bounds I have looked at Prof. Ripley's 2002 RNews article but cannot

Dear all, Apologies for this beginner's question. I have a variable Price, which is associated with factors Season and Crop, each of which have several levels. The Price variable contains missing values (NA), which I want to substitute by the mean of the remaining (non-NA) Price values of the same Season-Crop combination of levels. Price Crop Season 10 Rice Summer 12

I've got a problem with the sparseby command (reshape library), and I have reached the peak of my R knowledge (it isn't really that high). I have a small data frame of 23 rows and 15 columns, here is a subset, the first four columns are factors and the rest are numeric (only one, line54 is provided). bearID YEAR Season SEX line54 5 1900 8 3 0 16.3923519 11 2270