similar to: scale(x, center=FALSE) (PR#14219)

I found a problem with scale function, while using center=FALSE and scale=TRUE: all column are not divided by standard error, but divided by sqrt (1/(n-1) sum Xi^2 ) Example: > l<- c(1,2,3) > scale(l,F,T) [,1] [1,] 0.3779645 [2,] 0.7559289 [3,] 1.1338934 attr(,"scaled:scale") [1] 2.645751 2.645751 = sqrt( 1/2 * (1+4+9) ) Antoine Lucas & Aymeric Labourdette

[re-sending - previous email went out by accident before complete] Hi Joe, The centering and re-scaling is done for the purposes of his example, and also to be consistent with his definition of the sharpe function. In particular, note that the sharpe function has the rf (riskfree) parameter with a default value of .03/252 i.e. an ANNUAL 3% rate converted to a DAILY rate, expressed in decimal. That

Wrong list. Post on r-sig-finance instead. Cheers, Bert On Nov 20, 2017 11:25 PM, "Joe O" <joerodonnell at gmail.com> wrote: Hello, I'm trying to understand how to use the pbo package by looking at a vignette. I'm curious about a part of the vignette that creates simulated returns data. The package author transforms his simulated returns in a way that I'm

Hi Joe, The centering and re-scaling is done for the purposes of his example, and also to be consistent with his definition of the sharpe function. In particular, note that the sharpe function has the rf (riskfree) parameter with a default value of .03/252 i.e. an ANNUAL 3% rate converted to a DAILY rate, expressed in decimal. That means that the other argument to this function, x, should be DAILY

Hi, The documentation for scale() states:"If center is TRUE then centering is done by subtracting the column means (omitting NAs) of x from their corresponding columns". But it seems that R is subtracting something else instead of the column mean: > x=c(2,4,3,4,5) > mean(x) [1] 3.6 > x-mean(x) [1] -1.6 0.4 -0.6 0.4 1.4 > scale(x) [,1] [1,] -1.4032928 [2,]

Dear all, I found pls.pcr package will give different results if the data are centered and scaled using scale(). I am not sure about when I should scale my data, and whether the dependent variable should be scaled. If the dependent variable is scaled, how I give a prediction to the real data? I appreciate for any suggestions and comments. Best regards, Jinsong ===== (Mr.) Jinsong Zhao Ph.D.

Hi Eric, Thank you, that helps a lot. If I'm understanding correctly, if I?m wanting to use actual returns from backtests rather than simulated returns, I would need to make sure my risk-adjusted return measure, sharpe ratio in this case, matches up in scale with my returns (i.e. daily returns with daily sharpe, monthly with monthly, etc). And I wouldn?t need to transform returns like the

Correct Sent from my iPhone > On 21 Nov 2017, at 22:42, Joe O <joerodonnell at gmail.com> wrote: > > Hi Eric, > > Thank you, that helps a lot. If I'm understanding correctly, if I?m wanting to use actual returns from backtests rather than simulated returns, I would need to make sure my risk-adjusted return measure, sharpe ratio in this case, matches up in scale with

using an example from r online help > state <- c("tas", "sa", "qld", "nsw", "nsw", "nt", "wa", "wa", "qld", "vic", "nsw", "vic", "qld", "qld", "sa", "tas", "sa", "nt", "wa", "vic",

I do not understand, from a PCA point of view, the option center=F of prcomp() According to the help page, the calculation in prcomp() "is done by a singular value decomposition of the (centered and possibly scaled) data matrix, not by using eigen on the covariance matrix" (as it's done by princomp()) . "This is generally the preferred method for numerical accuracy"

Hi ! I've used the example given in the documentation for the prcomp function both in R and SPAD to compare the results obtained. Surprisingly, I do not obtain the same results for the coordinates of the principal composantes with these two softwares. using USArrests data I obtain with R : > summary(prcomp(USArrests)) Importance of components: PC1 PC2

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Content-Type: text/plain; charset="iso-8859-1" Content-Transfer-Encoding: 7bit X-Virus-Scanned: by amavisd-new X-Spam-Checker-Version: SpamAssassin 2.63 (2004-01-11) on hypatia.math.ethz.ch X-Spam-Level: **** X-Spam-Status: No, hits=4.2 required=5.0 tests=MSGID_FROM_MTA_HEADER,RCVD_IN_BL_SPAMCOP_NET autolearn=no version=2.63 Dear r-help list, my question is about ordination technics:

In the manual page for prcomp(), it says that sdev is "the standard deviations of the principal components (i.e., the square roots of the eigenvalues of the covariance/correlation matrix, though the calculation is actually done with the singular values of the data matrix)." ?However, this is not what I'm finding. ?The values appear to be the standard deviations of a reprojection of

Dear all here is my data called "rglp" structure(list(vzorek = structure(1:17, .Label = c("179/1/1", "179/2/1", "180/1", "181/1", "182/1", "183/1", "184/1", "185/1", "186/1", "187/1", "188/1", "189/1", "190/1", "191/1", "192/1",

Hi! (I'd like to be able to access your bugzilla, BTW) The documentation for parameter "adj" of text() in R 3.3.3 is hard to understand (unless you know what it does already): "adj one or two values in [0, 1] which specify the x (and optionally y) adjustment of the labels. On most devices values outside that interval will also work." What is the meaning of the values? I

Hi, I have a couple of observations, a question or two, and perhaps a suggestion related to the plotting of density on the y-axis within the hist() function when freq=FALSE. I was using the function and trying to develop an intuitive understanding of what the density is telling me. After reading through this fairly helpful post:

Hello Core Team, I sent this patch over a year ago. It looks like it was sent in response to another user's complaint which echoed some of my own observations about problems in the documentation for 'text'. Did anyone have a chance to look it over? I'd like to get it out of my queue. Thanks, Frederick On Tue, Apr 11, 2017 at 12:01:05PM -0700, frederik at ofb.net wrote: >

Hi, I am analysing gene expression data using the heatmap.2 function in R and I was wondering what is the formula of the "raw z-score" bar which shows the colors for each pixel. According to that post: https://mailman.stat.ethz.ch/pipermail/r-help/2006-September/113598.html, it is the (actual value - mean of the group) / standard deviation. But, mean of which group? Mean of the gene

Dear R-experts! I am currently running a meta-analysis with the help of the great metafor package. However I have some difficulties setting up my raw data to enter it to the meta-analysis models. I have a group of subjects that have been measured in two continuous variables (A & B). I have the information about the mean of the two variables, the group size (n) and the standard deviations of