similar to: Incoherence between arima.sim and auto.arima

>>>>> Serguei Sokol >>>>> on Wed, 19 Feb 2020 15:21:21 +0100 writes: > Hi, > I was bitten by a little incoherence in dimnames assignment or may be I > missed some point. > Here is the case. If I assign row names via dimnames(a)[[1]], when > nrow(a)=1 then an error is thrown. But if I do the same when nrow(a) > 1 >

If we change the behavior NULL--[[--assignment from `[[<-`(NULL, 1, "a" ) # gives "a" (*not* a list) to `[[<-`(NULL, 1, "a" ) # gives list("a") then we have more consistency there *and* your bug is fixed too. Of course, in other situations back-compatibility would be broken as well. Would that change the result of L <-

Hi, I was bitten by a little incoherence in dimnames assignment or may be I missed some point. Here is the case. If I assign row names via dimnames(a)[[1]], when nrow(a)=1 then an error is thrown. But if I do the same when nrow(a) > 1 it's OK. Is one of this case works unexpectedly? Both? Neither? a=as.matrix(1) dimnames(a)[[1]]="a" # error: 'dimnames' must be a list

>>>>> Martin Maechler >>>>> on Sat, 22 Feb 2020 20:20:49 +0100 writes: >>>>> William Dunlap >>>>> on Fri, 21 Feb 2020 14:05:49 -0800 writes: >> If we change the behavior NULL--[[--assignment from >> `[[<-`(NULL, 1, "a" ) # gives "a" (*not* a list) >> to >>

>>>>> William Dunlap >>>>> on Fri, 21 Feb 2020 14:05:49 -0800 writes: > If we change the behavior NULL--[[--assignment from > `[[<-`(NULL, 1, "a" ) # gives "a" (*not* a list) > to > `[[<-`(NULL, 1, "a" ) # gives list("a") > then we have more consistency there *and* your bug

>>>>> Martin Maechler >>>>> on Wed, 19 Feb 2020 18:06:57 +0100 writes: >>>>> Serguei Sokol >>>>> on Wed, 19 Feb 2020 15:21:21 +0100 writes: >> Hi, >> I was bitten by a little incoherence in dimnames assignment or may be I >> missed some point. >> Here is the case. If I assign row names

Hello to everyone! I have a question for you..I need to predict multivariate time series, for example sales of 2 products related one to the other, having the 2 prices like inputs.. Is there in R a function to do it? I saw dse package but I didn't find what a I'm looking for.. Could anyone help me? Thank you very much Giusy -- View this message in context:

i wonder about the following examples showing incoherence in how type conversions are done in r: x = TRUE x[2] = as.raw(1) # Error in x[2] = as.raw(1) : # incompatible types (from raw to logical) in subassignment type fix it seems that there is an attempt to coerce the raw value to logical here, which fails, even though as.logical(as.raw(1)) # TRUE likewise, x[2]

i wonder about the following examples showing incoherence in how type conversions are done in r: x = TRUE x[2] = as.raw(1) # Error in x[2] = as.raw(1) : # incompatible types (from raw to logical) in subassignment type fix it seems that there is an attempt to coerce the raw value to logical here, which fails, even though as.logical(as.raw(1)) # TRUE likewise, x[2]

I am trying to simulate time series data for an ar(1) and ma(1) process. I want the error term to have either a t distribution with 1 degree of freedom or a normal distribution with mean=0 and sd=1. Here is my code: error.model=function(n){rnorm(n,mean=0, sd=1)} data<-arima.sim(model=list(ar=c(0.1)), n=1000, n.start=200, start.innov=rnorm(200,mean=0, sd=1), rand.gen=error.model ) data

Hello, I have used the arima.sim function to generate a lot of time series, but to day I got som results that I didn't quite understand. Generating two time series z0 and z1 as eps <- rnorm(n, sd=0.03) z0 <- arima.sim(list(ar=c(0.9)), n=n, innov=eps) and z1 <- arima.sim(list(ar=c(0.9)), n=n, sd=0.03), I would expect z0 and z1 to be qualitatively similar. However, with n=10 the

Hi, I am using the arima.sim function to generate some AR time series. However, the function does not seem to produce exactly the same time series when I specify the innov parameter. For example > r <- rnorm(300) > x <- arima.sim(300, model=list(order=c(1,0,0),ar=c(.96)), innov=r, n.start=10) > y <- arima.sim(300, model=list(order=c(1,0,0),ar=c(.96)), innov=r, n.start=10) >

Hi Everyone, I'm having a problem with arima.sim. Namely specifying inital values for the series. If I generate a random walk > vs = rnorm(100,0,1) > xs = cumsum(vs) and fit an ARIMA(1,0,0) to it > xarima = arima(xs,order=c(1,0,0)) > xarima Call: arima(x = xs, order = c(1, 0, 0)) Coefficients: ar1 intercept 0.9895 8.6341 s.e. 0.0106 6.1869 I should

Hi, I have been using arima.sim from the stats package recently, and I'm wondering why I get different results when using what seem to be the same parameters. For example, I've given examples of three different ways to run arima.sim with what I believe are the same parameters. It's my understanding from the R documentation that rnorm is the default function for rand.gen if not

Recently I was using GAM and couldn't help noticing the following incoherence in prediction: > data(gam.data) > data(gam.newdata) > gam.object <- gam(y ~ s(x,6) + z, data=gam.data) > predict(gam.object)[1] 1 0.8017407 > predict(gam.object,data.frame(x=gam.data$x[1],z=gam.data$z[1])) 1 0.1668452 I would expect that using two types of predict arguments

Full_Name: Xiao Gang FAN Version: 2.4.0 OS: Windows XP Submission from: (NULL) (159.50.101.9) Dear All, This is not really a bug report, but rather a change wish to the Base R behaviour on some functions when applying them to character strings vectors/matrices. Actually in R, we can do thinks like, the most naturally way in this the world: > "a" < "b" [1] TRUE >

Rejoice! We have found a trick to make 830gm/845g stable at long last. Ever since the switch to GEM and dynamic video memory, those early second generation chipsets have been plagued by instability. The lack of flushing cachelines from the CPU to GMCH was eventually solved by using an undocmented bit, but 830/845 were still hanging under memory pressure. These deaths were all due to garbage

Dear all, I'm in basic setup of my network: I try to do a call from a softphone to an other one but I got the error 603 Declined. Below the sip.conf: *[gianca] type=friend username=gianca secret=pwd_gianca host=dynamic context=tutorial* *[giusy] type=friend username=giusy secret=pwd_giusy host=dynamic context=tutorial* extension.conf: *[tutorial] exten => 1234,1,Dial(SIP,gianca)* *exten

Hi Peter, On Mon, Jan 04, 2016 at 02:41:28PM +0100, Peter Zijlstra wrote: > On Thu, Dec 31, 2015 at 09:08:22PM +0200, Michael S. Tsirkin wrote: > > +#ifdef CONFIG_SMP > > +#define fence() metag_fence() > > +#else > > +#define fence() do { } while (0) > > #endif > > James, it strikes me as odd that fence() is a no-op instead of a > barrier() for UP, can

> > > For the example to work here the CSE pass itself needs to be > flow-sensitive and context-sensitive. I don't think that's how most > optimizations in LLVM work. If it is, then I agree with all you said. But > if it isn't, there's no point in bumping up the context sensitivity just > for the pointer analysis. > > As Daniel mentioned earlier in this