[R] Testing.

I have just changed my email address with the R-help mailing lists, and I want to check that things are working. Sorry for the noise. cheers, Rolf Turner -- Honorary Research Fellow Department of Statistics University of Auckland Stats. Dep't. (secretaries) phone: +64-9-373-7599

Re: [R] Testing for R CMD INSTALL

On 24/07/2021 11:22 a.m., Andrew Simmons wrote: Hello, I was wondering if anyone has a way to test if a package is currently being installed. My solution was to check if environment variable "R_INSTALL_PKG" was unset, something like: "R CMD INSTALL-ing" <- function ()

Re: [R] Testing for R CMD INSTALL

Does ?installed.packages help? 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 Sat, Jul 24, 2021 at 8:30 AM Andrew Simmons wrote: > Hello, > > > I was

[R] Testing for R CMD INSTALL

Hello, I was wondering if anyone has a way to test if a package is currently being installed. My solution was to check if environment variable "R_INSTALL_PKG" was unset, something like: "R CMD INSTALL-ing" <- function () !is.na(Sys.getenv("R_INSTALL_PKG", NA)) Unfortunately, I couldn't find

Re: [R] Testing optimization solvers with equality constraints

In case it is of interest this problem can be solved with an unconstrained optimizer, here optim, like this: proj <- function(x) x / sqrt(sum(x * x)) opt <- optim(c(0, 0, 1), function(x) f(proj(x))) proj(opt$par) ## [1] 5.388907e-09 7.071068e-01 7.071068e-01 On Fri, May 21, 2021

Re: [R] Testing optimization solvers with equality constraints

I meant: x0 = c (1, 1e-3, 0) Not: x0 = c (1, 1e6, 0) So, large intentional error may work too. Possibly, better...? On Thu, May 27, 2021 at 6:00 PM Abby Spurdle wrote: > > If I can re-answer the original post: > There's a relatively simple solution. > (For these problems, at least). > > #wrong

Re: [R] Testing optimization solvers with equality constraints

If I can re-answer the original post: There's a relatively simple solution. (For these problems, at least). #wrong x0 = c (1, 0, 0) NlcOptim::solnl(x0, objfun = f, confun = conf)$par Rdonlp2::donlp2(x0, fn = f, nlin = list(heq), nlin.lower = 0, nlin.upper = 0)$par #right x0 = c (1, 1e6, 0)

Re: [R] Testing optimization solvers with equality constraints

I need to retract my previous post. (Except the part that the R has extremely good numerical capabilities). I ran some of the examples, and Hans W was correct. __ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see

Re: [R] Testing optimization solvers with equality constraints

As someone who works on trying to improve the optimization codes in R, though mainly in the unconstrained and bounds-constrained area, I think my experience is more akin to that of HWB. That is, for some problems -- and the example in question does have a reparametrization that removes the

Re: [R] Testing optimization solvers with equality constraints

I received an off-list email, questioning the relevance of my post. So, I thought I should clarify. If an optimization algorithm is dependent on the starting point (or other user-selected parameters), and then fails to find the "correct" solution because the starting point (or other user-selected

Re: [R] Testing optimization solvers with equality constraints

Sorry, missed the top line of code. library (barsurf) __ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and

Re: [R] Testing optimization solvers with equality constraints

For a start, there's two local minima. Add to that floating point errors. And possible assumptions by the package authors. begin code f <- function (x, y, sign) { unsign.z <- sqrt (1 - x^2 - y^2) 2 * (x^2 - sign * y * unsign.z) } north.f <- function (x, y) f (x, y, +1) south.f <-

Re: [R] Testing optimization solvers with equality constraints

Yes. "*on* the unit sphere" means on the surface, as you can guess from the equality constraint. And 'auglag()' does find the minimum, so no need for a special approach. I was/am interested in why all these other good solvers get stuck, i.e., do not move away from the starting point. And how to

Re: [R] Testing optimization solvers with equality constraints

Sorry, this might sound like a poor question: But by "on the unit sphere", do you mean on the ***surface*** of the sphere? In which case, can't the surface of a sphere be projected onto a pair of circles? Where the cost function is reformulated as a function of two (rather than three) variables.

Re: [R] Testing optimization solvers with equality constraints

I might (and that could be a stretch) be expert in unconstrained problems, but I've nowhere near HWB's experience in constrained ones. My main reason for wanting gradients is to know when I'm at a solution. In practice for getting to the solution, I've often found secant methods work faster,

Re: [R] Testing optimization solvers with equality constraints

Hi Hans: I can't help as far as the projection of the gradient onto the constraint but it may give insight just to see what the value of the gradient itself is when the optimization stops. John Nash ( definitely one of THE expeRts when it comes to optimization in R ) often strongly recommends to

Re: [R] Testing optimization solvers with equality constraints

Mark, you're right, and it's a bit embarrassing as I thought I had looked at it closely enough. This solves the problem for 'alabama::auglag()' in both cases, but NOT for * NlcOptim::solnl -- with x0 * nloptr::auglag -- both x0, x1 * Rsolnp::solnp -- with x0 *

Re: [R] Testing optimization solvers with equality constraints

Hi Hans: I think that you are missing minus signs in the 2nd and 3rd elements of your gradient. Also, I don't know how all of the optimixation functions work as far as their arguments but it's best to supply the gradient when possible. I hope it helps. On Fri, May 21, 2021 at 11:01 AM Hans

[R] Testing optimization solvers with equality constraints

Just by chance I came across the following example of minimizing a simple function (x,y,z) --> 2 (x^2 - y z) on the unit sphere, the only constraint present. I tried it with two starting points, x1 = (1,0,0) and x2 = (0,0,1). #-- Problem definition in R f = function(x) 2 * (x[1]^2

[R] Testing.

My apologies for the noise. Please ignore this message. I am just trying to test out message filters in a new mail client that I am learning to use. Again, sorry for the noise. cheers, Rolf Turner -- Honorary Research Fellow Department of Statistics University of Auckland Phone:

Re: [R] Testing wether my dataset follows a poisson distribution with R

That is logically impossible. You can only show that there is insufficient evidence (according to whatever evidentiary criterion you have chosen) to show that the data were *not* a (iid or other) sample from a Poisson. This may seem esoteric, but it is not. (The simplest incantation is that you

Re: [R] Testing wether my dataset follows a poisson distribution with R

Your first check might be to see in the mean and sd are "reasonably" close. Next approach would be to see if the `qqplot` of that vector has an arguably straight-line relationship with a random draw from a Poisson random generator function with the same mean. ?rpois ?qqplot And do remember

[R] Testing wether my dataset follows a poisson distribution with R

Dear friends, I have a sample dataset, which is basically the number of transits through a particular waterway, and is on a daily basis. MyDat <- dataset$DailyTransits What I´d like to do is to test whether MyDat follows a poisson distribution or not. What R function could accomplish this? Any

Re: [R] testing my package : unstated dependency to self in package tests

That worked. Thanks. From: Michael Dewey Sent: Sunday, February 16, 2020 5:54 PM To: Servet Ahmet Çizmeli ; r-help@r-project.org Subject: Re: [R] testing my package : unstated dependency to self in package tests When something similar happened to me I found

Re: [R] testing my package : unstated dependency to self in package tests

I think the Posting Guide would call this the wrong mailing list for this question: should be on R-package-devel. On February 16, 2020 3:03:55 AM PST, "Servet Ahmet Çizmeli" wrote: >I am updating my CRAN package geoSpectral. I get the following Warning >during R CMD check : > >... >* checking

Re: [R] testing my package : unstated dependency to self in package tests

When something similar happened to me I found it went away when I added Suggests: to the DESCRIPTION file. Whether this will work for you I have no idea. Michael On 16/02/2020 11:03, Servet Ahmet Çizmeli wrote: I am updating my CRAN package geoSpectral. I get the following Warning during R

[R] testing my package : unstated dependency to self in package tests

I am updating my CRAN package geoSpectral. I get the following Warning during R CMD check : ... * checking for unstated dependencies in �tests� ... WARNING 'library' or 'require' call not declared from: �geoSpectral� All the .R files I have under the testhat directory begin by :

Re: [R] Testing for normality in categorical data

Hi Nancy, The chickwts dataset contains one sort-of continuous variable (weight) and a categorical variable (feed). Two things that will help you to understand what you are trying to do is to "eyeball" the "weight" data: # this shows you the rough distribution of chick weights

Re: [R] Testing for normality in categorical data

Categorical data cannot be normal. What you are doing is statistical nonsense, as your error messages suggest. You need to consult a local statistician for help. Furthermore, statistical questions are generally OT on this list, which is about R programming. Bert Gunter "The trouble with having

[R] Testing for normality in categorical data

Hello I have data that are categorical both independent variable and dependent as well having levels more than 3. How can i check the normality of my data? I have tried the example given of Shapiro-Wilk for levels of factors data summary(chickwts) ## linear model and ANOVA fm <- lm(weight ~

Re: [R] testing in spatial sure models

You could start by going to the CRAN website, clicking on the "Task Views" item on the left, then clicking on "Spatial". This will bring you to a page with extensive information about doing things with spatial data in R. It includes some brief descriptions of the purposes/capabilities of many

Re: [R] testing in spatial sure models

Wrong list. For statistical questions (which this is), post to stats.stackexchange.com. I suspect you will have to frame your query more coherently (context, model, etc.) to get a response even there. Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming

[R] testing in spatial sure models

Good afternoon, I would like to know how to test for homogeneity in spatial sure models. Thank you, Pilar Pilar González Casimiro Facultad de Ciencias Económicas y Empresariales Avda. Lehendakari Aguirre, 83 48015 Bilbao tfno: 94 601 3730 __

Re: [R] testing whether clusters in a PCA plot are significantly different from one another

Dear Micheal So I would be much better off just reporting the PCA as is and conclude what i can from plot cheers Julian Julian R. Marchesi Deputy Director and Professor of Clinical Microbiome Research at the Centre for Digestive and Gut Health, Imperial College London, London W2 1NY Tel:

Re: [R] testing whether clusters in a PCA plot are significantly different from one another

Significance tests for group differences in a MANOVA of lm(cbind(pc1, pc2) ~ group) will get you what you want, but you are advised DON'T DO THIS, at least without a huge grain of salt and a slew of mea culpas. Otherwise, you are committing p-value abuse and contributing to the notion that

Re: [R] testing whether clusters in a PCA plot are significantly different from one another

017 15:29 To: Marchesi, Julian; r-help@r-project.org Subject: RE: [R] testing whether clusters in a PCA plot are significantly different from one another In that case you should be able to use manova where pc1 and pc2 are the independent (response) variables and group (Baseline, HFD+

Re: [R] testing whether clusters in a PCA plot are significantly different from one another

: Marchesi, Julian [mailto:j.march...@imperial.ac.uk] Sent: Friday, January 6, 2017 9:02 AM To: David L Carlson Subject: Re: [R] testing whether clusters in a PCA plot are significantly different from one another Dear David The clusters are defined by the metadata which tells R where to draw the lines

[R] testing whether clusters in a PCA plot are significantly different from one another

Rplot_PCA.pdf Description: Rplot_PCA.pdf __ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide

Re: [R] Testing significance of individual regression slopes

You can't if I understand correctly: there is no individual subject regression coefficient, only a variance component for a random subject intercept. Do you mean that you want to "test" whether that component is nonzero ?(It is, of course). If so, IIRC, lmer eschews such tests for technical

[R] Testing significance of individual regression slopes

Hi R-help, I have an lmer logistic regression with a within subjects IV and subject as a random factor: model <- lmer(optimal_choice ~ level_one_value_difference + (1|subid), data = dat) What I want is to test if the individual subject regression coefficient is significantly different from 0.

Re: [R] Testing installed package of rJava in Linux

The variable DISPLAY is what is causing problems. Run the command 'unset DISPLAY' before running R . Stephen On 09/03/16 01:06 PM, Uwe Ligges wrote: > I do not get this: If it works it is OK to use it. If it does not work, > you can't > > Best, > Uwe Kigges > > > > > > On 09.03.2016

Re: [R] Testing installed package of rJava in Linux

I do not get this: If it works it is OK to use it. If it does not work, you can't Best, Uwe Kigges On 09.03.2016 17:44, Santosh wrote: Thanks for your response. Since the test failed due to X11 connectivity reasons, is it okay to use it in applications where X11 server connectivity is

Re: [R] Testing installed package of rJava in Linux

Thanks for your response. Since the test failed due to X11 connectivity reasons, is it okay to use it in applications where X11 server connectivity is not required? Thanks and much appreciated, Santosh On Tue, Mar 8, 2016 at 10:41 PM, Uwe Ligges wrote: > > > On

Re: [R] Testing installed package of rJava in Linux

On 09.03.2016 02:19, Santosh wrote: Dear Rxperts.. I installed rJava on 64-bit Linux system and apparently it installed without errors.However, I got the following error message when I tried to test the installed package.

[R] Testing installed package of rJava in Linux

Dear Rxperts.. I installed rJava on 64-bit Linux system and apparently it installed without errors.However, I got the following error message when I tried to test the installed package. Error in .jcall("RJavaTools",

[R] Testing a non-binary categorical variable with coxph and robust variance

__ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible

[R] Testing Restrictions on Beta (long-run coefficients), reproducible example

The code given below estimates a VEC model with 4 cointegrating vectors. It is a reproducible code, so just copy and paste into your R console (or script editor). nobs = 200 e = rmvnorm(n=nobs,sigma=diag(c(.5,.5,.5,.5,.5))) e1.ar1 = arima.sim(model=list(ar=.75),nobs,innov=e[,1]) e2.ar1 =

Re: [R] testing whether two character vectors contain (the same) items in the same order

On 8/6/2015 5:25 AM, Federico Calboli wrote: Hi All, let’s assume I have a vector of letters drawn only once from the alphabet: x = sample(letters, 15, replace = F) x [1] z t g l u d w x a q k j f n “v y = x[c(1:7,9:8, 10:12, 14, 15, 13)] I would now like to test how good a match y is

Re: [R] testing whether two character vectors contain (the same) items in the same order

And I probably should have included this link: http://journal.r-project.org/archive/2014-1/loo.pdf On 8/8/2015 12:50 PM, Robert Baer wrote: On 8/6/2015 5:25 AM, Federico Calboli wrote: Hi All, let’s assume I have a vector of letters drawn only once from the alphabet: x = sample(letters,

Re: [R] testing whether two character vectors contain (the same) items in the same order

On 7 Aug 2015, at 01:59, Bert Gunter bgunter.4...@gmail.com wrote: Boris: You may be right, but it seems like esp to me based on the op's non-description of likelihood of coming from the same noisy process. My response would be: seek local statistical help, as your replies indicate a

Re: [R] testing whether two character vectors contain (the same) items in the same order

On Aug 7, 2015, at 12:22 AM, Federico Calboli wrote: On 7 Aug 2015, at 01:59, Bert Gunter bgunter.4...@gmail.com wrote: Boris: You may be right, but it seems like esp to me based on the op's non-description of likelihood of coming from the same noisy process. My response would be:

[R] testing whether two character vectors contain (the same) items in the same order

Hi All, let’s assume I have a vector of letters drawn only once from the alphabet: x = sample(letters, 15, replace = F) x [1] z t g l u d w x a q k j f n “v y = x[c(1:7,9:8, 10:12, 14, 15, 13)] I would now like to test how good a match y is for x. Obviously I can transform the letters in

Re: [R] testing whether two character vectors contain (the same) items in the same order

Boris: You may be right, but it seems like esp to me based on the op's non-description of likelihood of coming from the same noisy process. My response would be: seek local statistical help, as your replies indicate a good deal of statistical confusion. Cheers, Bert On Thursday, August 6,

Re: [R] testing whether two character vectors contain (the same) items in the same order

Define goodness of match . For exact matches, see ?== , all.equal, etc. Bert On Thursday, August 6, 2015, Federico Calboli federico.calb...@helsinki.fi wrote: Hi All, let’s assume I have a vector of letters drawn only once from the alphabet: x = sample(letters, 15, replace = F) x [1] z

Re: [R] testing whether two character vectors contain (the same) items in the same order

You are looking for what is known as the Cayley distance between vectors - an edit distance that allows only transpositions. RSeek mentions PerMallows (https://cran.r-project.org/web/packages/PerMallows/PerMallows.pdf) and Rankluster

Re: [R] testing whether two character vectors contain (the same) items in the same order

On 6 Aug 2015, at 15:40, Bert Gunter bgunter.4...@gmail.com wrote: Define goodness of match . For exact matches, see ?== , all.equal, etc. Fair point. I would define it as a number that tells me how likely it is that the same (noisy) process produced both lists. BW F Bert On

Re: [R] Testing for significant differences between groups in multiple linear regression

Look no further! The answer is yes. However, if you are interested in why your query is probably nonsense and why overall tests of significance are a **really bad idea** in most scientific contexts (imho, anyway), then I suggest you post to a statistical list like stats.stackexchange.com . ...

[R] Testing for significant differences between groups in multiple linear regression

Dear R-colleagues, I am looking for a way to test whether one regression has significant different coefficients and overall results for 10 groups (grouping variable is irr). *What I have* The regression is: Depend = temp + temp² + perc + perc² + conti è split up for multiple groups of irr

Re: [R] Testing general hypotheses on regression coefficients

On Sunday, September 7, 2014 5:47 PM, peter dalgaard pda...@gmail.com wrote: On 06 Sep 2014, at 12:24 , bonsxanco bonsxa...@yahoo.com wrote: 1) 8th grade algebra tells me B2/B1 == 0 == B2 =0; EViews (econometrics program) doesn't have the same opinion: Wald test on my real

Re: [R] Testing general hypotheses on regression coefficients

On Monday, September 8, 2014 6:46 PM, Greg Snow 538...@gmail.com wrote: [very good suggestions] Thank you Greg for dedicating some time to my problem and giving advice on how I can tackle the issue. It is very appreciated. Unfortunately I think I will use another program for my original

Re: [R] Testing general hypotheses on regression coefficients

Others have discussed some of the theoretical approaches (delta method), but as has also been pointed out, this is a mailing list about R, not theory, so here are some approaches to your question from the approach of those of us who like programming R more than remembering theory. I assume that

Re: [R] Testing general hypotheses on regression coefficients

On 06 Sep 2014, at 12:24 , bonsxanco bonsxa...@yahoo.com wrote: 1) 8th grade algebra tells me B2/B1 == 0 == B2 =0; EViews (econometrics program) doesn't have the same opinion: Wald test on my real model (edited): * H0: B3/B2 = 0 - F-stat = 37.82497 * H0: B3 = 0- F-stat =

Re: [R] Testing general hypotheses on regression coefficients

Hi Chris, On Fri, Sep 5, 2014 at 7:17 PM, Chris bonsxa...@yahoo.com wrote: Hi. Say I have a model like y = a + B1*x1 + B2*x2 + B3*x3 + B4*x4 + e and I want to test H0: B2/B1 = 0 As noted by Bert, think about this. or H0: B2/B1=B4/B3 (whatever H1). How can I proceed? I now about

Re: [R] Testing general hypotheses on regression coefficients

Hi. First of all, thanks to all who have replied. 1) 8th grade algebra tells me B2/B1 == 0 == B2 =0; EViews (econometrics program) doesn't have the same opinion: Wald test on my real model (edited): * H0: B3/B2 = 0 - F-stat = 37.82497 * H0: B3 = 0- F-stat = 16.31689 2) I suspect you

Re: [R] Testing general hypotheses on regression coefficients

Scott said: car::deltaMethod I said: I just gave a quick look and searched about delta method, but I can't see how it would help in testing the restrictions above. Actually it seems that it should be the way to go: I just noticed under the EViews Wald test window the message Delta method

[R] Testing general hypotheses on regression coefficients

Hi. Say I have a model like y = a + B1*x1 + B2*x2 + B3*x3 + B4*x4 + e and I want to test H0: B2/B1 = 0 or H0: B2/B1=B4/B3 (whatever H1). How can I proceed? I now about car::linearHypothesis, but I can't figure out a way to do the tests above. Any hint? Thanks. C

Re: [R] Testing general hypotheses on regression coefficients

with a parametric bootstrap test. Just ideas. Good luck. Søren -Original Message- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of Chris Sent: 6. september 2014 04:17 To: r-h...@stat.math.ethz.ch Subject: [R] Testing general hypotheses on regression

Re: [R] Testing general hypotheses on regression coefficients

Well: 1) 8th grade algebra tells me B2/B1 == 0 == B2 =0; 2) I suspect you would need to provide more context for the other, as you may be going about this entirely incorrectly (have you consulted a local statistician?): your nonlinear hypothesis probably can be made linear under the right

[R] testing and comparing transformations to get a gaussian distribution

Hi guys, I distinctly remember having used an R toolbox that compared different transformation with regard to normality stats in the past, can’t find anything on google. Does anybody have a clue? Thanks, Diederick __ R-help@r-project.org mailing

Re: [R] testing and comparing transformations to get a gaussian distribution

There is the boxcox function in the MASS package that will look at the Box Cox family of transformations. On Mon, Jun 2, 2014 at 9:15 AM, Diederick Stoffers d.stoff...@gmail.com wrote: Hi guys, I distinctly remember having used an R toolbox that compared different transformation with regard

Re: [R] Testing parallel regression assumption

Hello, Take a look at http://stats.stackexchange.com/questions/58772/brant-test-in-r Hope this helps, Rui Barradas Em 19-05-2014 01:40, caoweina escreveu: Dear Rose : I saw your questions about the R function that performs brant test. Have you worked out ? Please give some advice. I

[R] Testing parallel regression assumption

Dear Rose : I saw your questions about the R function that performs brant test. Have you worked out ? Please give some advice. I need to do the brant test in R . Thank you very much! sincerely! Anna __

Re: [R] Testing correlation of equation in a SUR model fitted by systemfit

Dear Paul On 15 April 2014 19:23, Paul Smith phh...@gmail.com wrote: How to test whether the correlation in the matrix of correlation of a two-equations SUR model fitted by package systemfit are significant? You can use a likelihood-ratio test to compare the SUR model with the corresponding

[R] Testing correlation of equation in a SUR model fitted by systemfit

Dear All, How to test whether the correlation in the matrix of correlation of a two-equations SUR model fitted by package systemfit are significant? Thanks in advance, Paul __ R-help@r-project.org mailing list

[R] Testing simple slopes for cross-level interactions

Hello, I would like to probe a significant 2-way, cross-level interaction effect from a linear mixed effects model that I ran using nlme. My model is as follows: mlmmodel - lme(fixed = RegDiseng ~ Happy + TraitHAPPYmean + Happy*TraitHAPPYmean, random = ~ Happy | ID, data = data,

[R] testing xts values in if command?

Dear all , xts objects give error in if command : Error in if : missing value where TRUE/FALSE needed library(quantmod) getSymbols(SPY) SPY[2007-01-03]$SPY.Adjusted SPY[2007-01-04]$SPY.Adjusted [,1] If I use as.numeric function it works : SPY[2007-01-03]$SPY.Adjusted

Re: [R] testing xts values in if command?

On Wed, Jan 29, 2014 at 1:25 PM, ce zadi...@excite.com wrote: Dear all , xts objects give error in if command : Error in if : missing value where TRUE/FALSE needed library(quantmod) getSymbols(SPY) SPY[2007-01-03]$SPY.Adjusted SPY[2007-01-04]$SPY.Adjusted [,1] If I use

Re: [R] testing if xts date exists ?

You can use the which.i argument to [.xts: is.null(SPY[2009-01-18,which.i=TRUE]) [1] TRUE Best, -- Joshua Ulrich | about.me/joshuaulrich FOSS Trading | www.fosstrading.com On Sat, Jan 25, 2014 at 9:27 AM, ce zadi...@excite.com wrote: Dear all How to test if xts date exists ? is.null

[R] testing if xts date exists ?

Dear all How to test if xts date exists ? is.null doesn't work. SPY[2009-01-18] doesn't exist but I can't catch it in my script. library(quantmod) getSymbols(SPY) SPY[2009-01-16] SPY.Open SPY.High SPY.Low SPY.Close SPY.Volume SPY.Adjusted 2009-01-1685.8685.99 83.05

Re: [R] testing if xts date exists ?

!length(SPY[2009-01-18]) #[1] TRUE   !length(SPY[2009-01-16]) #[1] FALSE #or  !nrow(SPY[2009-01-16]) A.K. On Saturday, January 25, 2014 10:27 AM, ce zadi...@excite.com wrote: Dear all How to test if xts date exists ? is.null doesn't work.  SPY[2009-01-18] doesn't exist but I can't catch it

Re: [R] testing for bimodal and for dip in between modes in R

Testing for bimodality is rather testing for unimodality. Hartigan and Hartigan (1985) presented the Dip-Test which is implemented in the R package DipTest with a much better approximation of the test distribution. If the test statistic is too high unimodality is rejected. To estimate the dip

[R] testing for bimodal and for dip in between modes in R

Hi I have distributions that are typically bimodal (see attached .pdf), and I would like to test for bimodality, and then estimate the point between the two modes, the dip in the distributions. any help would be greatly appreciated. thanks felix m66.junction.aln.pairwise.histogram.pdf

[R] Testing.

Please ignore. My apologies for the noise. cheers, Rolf Turner __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented,

[R] Testing custom linear contrasts with Welch correction (anova function)

Dear R users, I am doing custom contrasts with R (comparison of group means). Everything works fine, but I would like to test the 3 contrasts with and without a Welch correction for unequal variances. I can replicate SPSS results when equal variances are assumed, but I do not manage to test

Re: [R] Testing for weak exogeneity in a SUR ECM

Dear Kathrinchen It seems to me that your question is about statistics rather than about R and systemfit. If you find out how the statistical test should be conducted theoretically, I can probably advise you how to implement the test in R (systemfit). Best wishes, Arne On 11 July 2013 13:21,

[R] Testing of Diagnostic residuals in R

Hi there,  I want to ask a question about any function in r that helps test residuals of   the vector error correction model. I find it on Pfaff(2008) but he tests only residual for VAR(vector autoregressive model). I need to workout Portmanteau test, Normality test and Heteroskedasticty for

[R] Testing for weak exogeneity in a SUR ECM

Dear all, I have set up a Labour Demand Error Correction Model for some German federal states. As I expect the labour markets to be correlated I used a Seemingly Unrelated Regression using systemfit in R. My Model is: d(emp)_it = c + alpha*ln(emp)_i,t-1 + beta_1*ln(gdp)_i,t-1 + +

[R] Testing for significance of overlap in three sets - mantelhaen test?

Hi, My apologies for the naive question! I have three overlapping sets and I want to find the probability of finding a larger/greater intersection for 'A intersect B intersect C' (in the example below, I want to find the probability of finding more than 135 elements that are common in sets A, B

Re: [R] Testing for significance of overlap in three sets - mantelhaen test?

As this seems to be a statistics, not an R, question, it is off topic here. Post on a statistics list like stats.stackexchange.com instead. -- Bert On Tue, Mar 12, 2013 at 6:22 AM, Brian Smith bsmith030...@gmail.com wrote: Hi, My apologies for the naive question! I have three overlapping

[R] testing the multiple regression model

Hi I have 25 samples in my dataset. I have written a multiple regression model and I would like to test it. I would like to train my model on 20 samples and then test it on 5 remaining. However I would like to test the model several times, each time using different 5 samples out of 25 and check

Re: [R] Testing continuous zero-inflated response

On Sun, 27 Jan 2013, Kay Cichini wrote: That said, wilcox_test(x ~ factor(y), distribution = exact) or the same with oneway_test, i.e would be ok? Yep, exactly. And you could also look at chisq_test(factor(x 0) ~ factor(y), distribtuion = approximate()) or something like that. Or

Re: [R] Testing continuous zero-inflated response

Many thanks - this was very helpful! Regards, Kay Am 28.01.2013 13:19 schrieb Achim Zeileis achim.zeil...@uibk.ac.at: On Sun, 27 Jan 2013, Kay Cichini wrote: That said, wilcox_test(x ~ factor(y), distribution = exact) or the same with oneway_test, i.e would be ok? Yep, exactly.

Re: [R] Testing continuous zero-inflated response

Thanks for the reply! Still, aren't there issues with 2-sample test vs y and excess zeroes (-many ties), like for Mann-Whitney-U tests? Kind regards, Kay 2013/1/26 Achim Zeileis achim.zeil...@uibk.ac.at On Fri, 25 Jan 2013, Kay Cichini wrote: Hello, I'm searching for a test that applies

Re: [R] Testing continuous zero-inflated response

On Sun, 27 Jan 2013, Kay Cichini wrote: Thanks for the reply! Still, aren't there issues with 2-sample test vs y and excess zeroes (-many ties), like for Mann-Whitney-U tests? If you use the (approximate) exact distribution, that is no problem. The problem with the Wilcoxon/Mann-Whitney

Re: [R] Testing continuous zero-inflated response

That said, wilcox_test(x ~ factor(y), distribution = exact) or the same with oneway_test, i.e would be ok? 2013/1/27 Achim Zeileis achim.zeil...@uibk.ac.at On Sun, 27 Jan 2013, Kay Cichini wrote: Thanks for the reply! Still, aren't there issues with 2-sample test vs y and excess zeroes

[R] Testing continuous zero-inflated response

Hello, I'm searching for a test that applies to a dataset (N=36) with a continuous zero-inflated dependent variable and only one nominal grouping variable with 2 levels (balanced). In fact there are 4 response variables of this kind which I plan to test seperately - the amount of zeroes ranges

Re: [R] Testing continuous zero-inflated response

On Fri, 25 Jan 2013, Kay Cichini wrote: Hello, I'm searching for a test that applies to a dataset (N=36) with a continuous zero-inflated dependent variable In a regression setup, one can use a regression model with a response censored at zero. survreg() in survival fits such models,

[R] Testing proportional odds assumption in R

Hi, M1 and M2 are extreme in that all or none of the variables have parallel lines on the logit scale. One can try fitting a partial POM, which remains fraught (but not as much as M2) because if the lines intersect for a particular variable where the data lie then there will be numerical

[R] Testing proportional odds assumption in R

I want to test whether the proportional odds assumption for an ordered regression is met. The UCLA website points out that there is no mathematical way to test the proportional odds assumption (http://www.ats.ucla.edu/stat//R/dae/ologit.htm), and use graphical inspection (We were unable to locate

[R] Testing the equality of two variances

Dear R-User, I met the problem to test equality of variance. Two sample units: conjps-c(9.41,10.45,10.78,10.73,11.11,11.12,11.59,11.04,11.63) ms-c(4.11,5.10,5.70,6.46,6.04,6.16, 6.24,6.32,7.33) Then I use the F test to test: •Test Equality of Two Variances F test to compare two variances

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