search for: parametrisation

...rcept) EV I(EV^2) -0.9015283 2.8774032 -0.1936074 but the predictions are the same (except for some rounding): table (round (predict (lm.ord), 6) == round (predict (lm.pol), 6)) TRUE 15 I thus conclude that the two models are the same and are just using a different parametrisation. I can easily interprete the parameters of the explicit polynomial but I started to wonder about the parametrisation of the ordered factor. In search of an answer, I did check the contrasts: contr.poly (levels (ordered (example.df$EV))) .L .Q [1,] -7.071068e-01 0.4082483 [...

...> > Bert Gunter > > "The trouble with having an open mind is that people keep coming along and > sticking things into it." > -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) It's a *little* bit R-ish in that the results depend on the parametrisation of the model which by default in R is formed using the so-called "treatment" contrasts. To wander from R into statistics (sorry Bert) the problem arises because the "usual" parametrisation of the model is the "over-parametrised" form: Y_ij = mu + beta_i + E_ij (i =...

This is really a statistical issue. What do you think the Intercept term represents? See ?contrasts. Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Thu, Feb 15, 2018 at 5:27 PM, Marc Girondot via R-help < r-help at

Dear R-er, I try to get the standard error of fitted parameters for factors with a glm, even the reference one: a <- runif(100) b <- sample(x=c("0", "1", "2"), size=100, replace = TRUE) df <- data.frame(A=a, B=b, stringsAsFactors = FALSE) g <- glm(a ~ b, data=df) summary(g)$coefficients # I don't get SE for the reference factor, here 0:

Hi list, Reading the thread "can a class require an other class?" it''s been mentioned that perhaps one way forward for the Puppet language is to phase out the include keyword in favour of parametrised classes. I''m thinking of my Puppet and the several levels of include chaining I use and I''m wondering how on earth that''d be possible. Maybe

Dear listers, I have written a function to facilitate the drawing of altitude profiles with x (distance), y (altitude) and a z parameter (altitude magnification). profplot<-function(x,y,z=10,...){ op <- par()$mai par(mai=c(0.95625,0.76875,0.76875,0.95625)) plot(x,y*z, type="l",asp=1,las=1,xlab="",ylab="",yaxt="n",...)

In Venables \& Ripley 3rd edition (p. 231) the proportional odds model is described as: logit(p<=k) = zeta_k + eta but polr apparently thinks there is a minus in front of eta, as is apprent below. Is this a bug og a feature I have overlooked? Here is the naked code for reproduction, below the results. ------------------------------------------------------------------------ --- version

This is the situation I have: All my hosts are the* same OS.* All my host are in the* same puppet environment,* so I cannot use %{environment} I have a module that sets all the *basic* functionality for the OS, resolution, authentication, security, packages, etc I have a module for each application hosted. At the moment all the ''data'' is in Puppet, mostly in parametrised

...hough the principle is sound. > But it must be target-dependent as for example on Power a > seq_cst store has a fence before it, while on ARM it has a fence > both before and after it (per http://www.cl.cam.ac.uk/~pes20/cpp/cpp0xmappings.html) That certainly seems to suggest some kind of parametrisation. > For this exact reason, I am planning on splitting AtomicExpandLoadLinkedPass > in a target-independent and a target-dependent file: the current pass claims > to be target-independent but is actually designed for ARM: for example it > puts a release-fence before a seq_cst CAS, which...

Dear Sir/Madam: this is shuangge Ma, graduate student in UW-Madison statistics department. I have a computational question. I have a function f(x,y). I want to find the y(x) that maximize f(x,y) under the constraint y(x) is a non-decreasing step function. Is there any R package or algorithm I can use for this purpose? thanks a lot for your time and help, Sincerely, Shuangge Ma

I am learning glm function, but how do you fit data using exponential distribution with glm? In the help file, under "Family Objects for Models", no ready made option seems available for the distribution as well as for other distributions satisfying GLM requirements not listed there.

How about: nis.na <- complete.cases --- From: <Ted.Harding at nessie.mcc.ac.uk> Hi Folks, My recent response to Laura Quinn's query about matrix subsetting reminded of a question. I wrote: iDir <- ((Winds[,20]<45)|(Winds[,20]>315))&(!is.na(Winds[,20])) Now, I find "!is.na" a bit awkward to type, so I might prefer to type it as "nis.na".

Hi, To simplify, suppose I have 2 observations each day for three days. I would like to define the correlation structure of these 6 observations as follows: the correlation of 2 observations on the same day is, say, alpha, the correlation for 2 observations one day apart is rho and the correlation for 2 observations 2 days apart is rho^2. I.e. I would like to have an AR1 correlation + a

Hi All, I'm trying to use one of the (2D) numerical integration functions, which is not where the problem is. The function definition is as follows: adaptIntegrate(f, lowerLimit, upperLimit, ...) The problem is that I want to integrate a 3D function which has been parametrised such that it is a 2D function: eg. I want to integrate f(x_start+gradient_x*t1, y_start+gradient_y*t2) for t1 in

Hi, Is it possible to redirect passing multi dimensional parameters? I need to send params[:current][:selview] to another action mantaining the same data structure if I try as follows: redirect_to :controller=>"main",:action=>"inquiry",{"current"=>{ "selview"=>params[:current][:selview]}} I receive "syntax error, unexpected

...agleffler/ Please report issues and bugs at https://github.com/strakaps/MittagLeffleR/issues Vignettes: - plots of CDF and PDF: https://cran.r-project.org/web/packages/MittagLeffleR/vignettes/MLdist.html - random variable generation: https://cran.r-project.org/web/packages/MittagLeffleR/vignettes/parametrisation.html - calculation of quantiles: https://cran.r-project.org/web/packages/MittagLeffleR/vignettes/probsNquantiles.html Thanks! -- * Dr Peter Straka* *Research Fellow (DECRA), School of Physical Engineering and Mathematical Sciences* UNSW Canberra Campbell ACT 2600 Australia H: strakaps.github.io...

...a plane (x,y). The only way I could think of is to compute the convex hull of the (x,y) coordinates of each object and use this as the outline of the object. This is clearly not very efficient or satisfying. I think I'm on the wrong track from the start. Is there an obvious analytical parametrisation of such projections? Any comments are welcome. Many thanks, baptiste > > rotM3d <- function(theta=0, phi=0, psi=0){ # 3D rotation matrix > a11 <- cos(psi)*cos(phi) - cos(theta)*sin(phi)*sin(psi) > a12 <- cos(psi)*sin(phi) + cos(theta)*cos(phi)*sin(psi) > a13 <- si...

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Hello! I would like to use constrain to sum coeficients of a factor to 0 instead of classical corner contraint i.e. I would like to fit a model like lm(y ~ 1 + effectA + effectB) and say get parameters intercept effectA_1 effectA_2 effectB_1 effectB_2 effectB_3 where effectA_1 represents deviation of level A_1 from intercept and sum(effectA_1, effectA_2) = 0 and the same for factor B. Is

Hello, I'm a grad student in the Intelligent Transportation Systems lab at Portland State Univ. in Portland, OR, USA. I'm trying to learn the basics of R to run a negative binomial in the near future, and so I ran a test regression on roadway crash data obtained from "Statistical and Econometric Methods for Transportation Data Analysis" by Washington et al (p. 250). I ran the