similar to: R-specific environment variables: Naming convention?

Hi all, I wanto to run a plot about the levels of a variable parting on an ols regression. The regression in done on the rate of return of the variable. Imagine R_{t}=a+b*R_{t-1} So If P, the "estimated" price would be P_{t}=P_{t-1}*R_{t} Imagine that I obtain lm fitted values and the original R_{t}, R_{t-1} are [1000,1] dimmension... How it is posible to obtain also 1000,1 fitted

i have loop index I. I want to increment it by 1. How to do this in registerinfo.td. I m trying following but getting error. let SubRegIndices = [sub_32bit, sub_32bit_hi], CoveredBySubRegs = 1 in { foreach I = 0-255 in { m=add(I,1); def R_#J#_REG64b_#I : R_P<"R_"#J#"_R64b_"#I, !shl(I,2), [!cast<R_P>("R_"#J#"_REG32b_"#I),

I am trying to create a set of wavelets in frequency space--namely Cauchy wavelets for an intensity analysis (von Tscharner, 2000). The wavelets are defined by the following formula: [(f/cf)^(cf*scale)]*[e^((-f/cf)+1)^(cf*scale)] where *f *is frequency of length *n*, *cf* is center frequency (defined below) and is an array of *j *columns and *n* row, and scale is a constant. cf = (1/scale)*(j

I have a long equation that I need to break in the R documentation of a package or it trails off the right hand side of the page. Here's the formula: \deqn{Cov(r_{ist}, r_{iuv})= [.5\rho_{ist}\rho_{iuv}(\rho_{isu}^2 + \rho_{isv}^2 + \rho_{itu}^2 + \rho_{itv}^2) + \rho_{isu}\rho_{itv}+ \rho_{isv}\rho_{itu}-(\rho_{ist}\rho_{isu}\rho_{isv} + \rho_{its}\rho_{itu}\rho_{itv}) +

I noticed that in https://svn.r-project.org/R/trunk/src/library/stats/R/loess.R that we are now calling R_loess_raw, R_lowesw, R_lowesp, etc. I'm interested to know what is the benefit/reason for the 'R_', as I am unfamiliar with this prefix and do not see it mentioned in 'Writing R Extensions.' Thanks, Ben

On Sun, Jul 31, 2011 at 3:04 PM, Jianzhou Zhao <jianzhou at seas.upenn.edu> wrote: > The current memory model section ends with the following discussions: > > "Note that in cases where none of the atomic intrinsics are used, this > model places only one restriction on IR transformations on top of what > is required for single-threaded execution: introducing a store to a

The current memory model section ends with the following discussions: "Note that in cases where none of the atomic intrinsics are used, this model places only one restriction on IR transformations on top of what is required for single-threaded execution: introducing a store to a byte which might not otherwise be stored to can introduce undefined behavior.... " Why is introducing

On Sun, Jul 31, 2011 at 7:11 PM, Eli Friedman <eli.friedman at gmail.com> wrote: > On Sun, Jul 31, 2011 at 3:04 PM, Jianzhou Zhao <jianzhou at seas.upenn.edu> wrote: >> The current memory model section ends with the following discussions: >> >> "Note that in cases where none of the atomic intrinsics are used, this >> model places only one restriction on

For some further information, on compiling with rtools, using the following scripts, https://github.com/r-windows/r-base, I receive a segfault: installing 'sysdata.rda' building package 'compiler' byte-compiling package 'compiler' byte-compiling package 'base' byte-compiling package 'tools' sh: line 3: 3614 Done ( cat

This came up on r-help but indicates a bug. dnbinom(x,n,p) calls dbinom_raw(n-1,...) which returns 0 for n<1. -thomas ---------- Forwarded message ---------- Date: Thu, 08 Feb 2001 17:10:23 +0000 From: Yudi Pawitan <yudi@stat.ucc.ie> To: Mark Myatt <mark@myatt.demon.co.uk> Cc: R-Help <r-help@stat.math.ethz.ch> Subject: Re: [R] Goodness of fit to Poisson / NegBinomial

for a silly question, wondering how to test fit with the one sample as follow. I have read _fitting distributions with R_, but that doesn't answer my specific question. inclined to use Kolmogorov-Smirnov D, and its associative p value. much appreciation! X20.001 232 93 84 185 336 417 228 199 2110 1411 612 1913 1314 3015

Dear all, I have a somewhat unusual linear mixed model that I can't seem to code in lme. It's only unusual in that one random effect is applied only to some of the observations (I have an indicator variable that specifies which observations have this random effect). The model is: X_hijk = alpha_h + h * b_i + r_(ij) + e_hijk , where h = 0 or 1 (indicator) i = 1, ..., N j = 1,

I use Samba 3.0.23d at FreeBSD 4.11-RELEASE-p25 as PDC and sometimes Microsoft Workgroup Add-On for MS-DOS and Mail as client. At FreeBSD box I have directory /common/install/postgreSQL and symlink to it: /usr/export/XP/i386/\$oem\$/install/postgreSQL -> /common/install/postgreSQL The path /usr/export/XP shared for MS Network as XP and mount via net use X: \\my_server\XP. So files and

Do your 32768 registers also have sub registers? I can't tell you exactly what to change. I'm not familiar with the code. I would just be running grep or something. ~Craig On Fri, Jul 14, 2017 at 10:23 AM, hameeza ahmed <hahmed2305 at gmail.com> wrote: > Thank you so much. I think there is no issue with my definitions since i > have to use larger registers i.e 65536 bit

For reasons which I'll spare you, I'm writing a program to analyse R source code. This has led me to probe some of the darker corners of R syntax to find out what is supposed to happen. Now, from reading the R documentation (and the New S book &c) I know perfectly well that f(a, b, etc) <- x is supposed to turn into a <- "f<-"(a, b, etc, value=x) Except,

Hello r-help, As far as I've seen, there is no function in R dedicated to sampling from a discrete distribution with a specified mass function. The standard library doesn't come with anything called rdiscrete or rpmf, and I can't find any such thing on the cheat sheet or in the Probability Distributions chapter of _An Introduction to R_. Googling also didn't bring back anything.

I have made changes in 3 files: LaneBitmask.h, codegenregisters.cpp and miparser.cpp. files are attached here. Now i am getting following errors. which means registerinfo.inc file is not generated successfully. /PIM/lib/Target/X86/MCTargetDesc/X86BaseInfo.h:733:24: error: no member named 'XMM8' in namespace 'llvm::X86' if ((RegNo >= X86::XMM8 && RegNo <=

An additional 1000 packages have been added to CRAN. This time, it took less than 6 months. Today (August 22, 2016), the Comprehensive R Archive Network (CRAN) [1] reports: ?Currently, the CRAN package repository features 9004 available packages.? The rate with which new packages are added to CRAN is increasing. During 2007-2009 we went from 1000 to 2000 packages in 906 days (1.1 per day) and

CRAN reached 12,000 packages [1] today (December 15, 2017). A huge thank you to the CRAN team! Milestones: 2017-12-15 12000 pkgs (+6.1/day over 165 days) 6910 mnts (+3.2/day) 2017-07-04 11000 pkgs (+6.3/day over 159 days) 6377 mnts (+3.3/day) 2017-01-27 10000 pkgs (+6.3/day over 158 days) 5845 mnts (+3.5/day) 2016-08-22 9000 pkgs (+5.7/day over 175 days) 5289 mnts (+5.8/day) 2016-02-29 8000

Another 1000 packages were added to CRAN, which took less than 7 months. Today (February 29, 2017), the Comprehensive R Archive Network (CRAN) [1] reports: ?Currently, the CRAN package repository features 8002 available packages.? The rate with which new packages are added to CRAN is increasing. In 2014-2015 we had 1000 packages added to CRAN in 355 days (2.8 per day), the following 1000