similar to:

Hello, I'm trying to do two things: -1. Ensure that I understand how quantmod adjust's OHLC data -2. Determine how I ought to adjust my data. My overarching-goal is to adjust my OHLC data appropriately to minimize the difference between my backtest returns, and the returns I would get if I was trading for real (which I'll be doing shortly). Background: -1. I'm using Alpha

Hi, I am a new user of R and this is my first e-mail here. Please enlighten me on any etiquette issues I may have overstepped on. My questions is as follows: I need to do some data analysis for data from .csv files for stocks (that I have obtained from yahoo) How can I do a "smart update" of this data from Yahoo (or any other site if you wish), so that in some way, I do not have to

Hello, I am learning to use the metafor package to conduct meta-regression analyses for a systematic review on multidisciplinary care interventions in chronic kidney disease. For the forest plots, I can't figure out how to plot unadjusted and adjusted models on the same plot. From top to bottom, I would like to be able have the unadjusted plot, the multivariate adjusted plot, then each

Hello, Thank you for your help/advice! The issue here is speed/efficiency. I can do what I want, but its really slow. The goal is to have the ability to do calculations on my data and have it adjusted for look-ahead. I see two ways to do this: (I'm open to more ideas. My terminology: Unadjusted = values not adjusted for look-ahead bias; adjusted = values adjusted for look-ahead bias.) 1) I

Hello, Does anyone know of a way I can speed this up? Basically I'm attempting to get the data item on the same row as the report date for each report date available. In reality, I have over 11k of columns, not just A, B, C, D and I have to do that over 100 times. My solution is slow, but it works. The loop is slow because of merge. # create sample data z.dates =

Hello, I am relatively new to using R. I am using R version 2.8.0. I have a program that downloads stock data from Yahoo! Finance and stores it to a text file on my hard drive. The text file contains the date, opening price, high price, low price, closing price, volume and adjusted price (i.e., adjusted for dividends and splits). I want to read and manipulate the data in R. However, when I

Hi All, I have a dataframe, divs, that looks like this: > divs date ticker dividend 263 20010322 ADBE 0.025 264 20010628 ADBE 0.025 265 20010927 ADBE 0.025 4308 20010212 ED 0.550 4309 20010514 ED 0.410 5416 20010330 GE 0.137 5417 20010629 GE 0.137 5418 20010928

Hi, This is probably trivial to most people out there, but I'm struggling with this. I have a data set which contains the closing prices (properly adjusted for dividends and splits) for several hundred securities and the closing prices for a general stock market index (S&P 500). I have no problem getting it into R with RODBC and manipulating it. There are no missing values. I can

# Hi all, # trying to run the following example code # from 'RQuantLib' package... HullWhite <- list(term = 0.055, alpha = 0.03, sigma = 0.01, gridIntervals = 40) Price <- rep(as.double(100),24) Type <- rep(as.character("C"), 24) Date <- seq(as.Date("2006-09-15"), by = '3 months', length = 24) callSch <- data.frame(Price, Type,

I'm trying to implement a recursive function using integrate, and I suspect I need a Vectorize somewhere, but I can't suss it out. Any help would be appreciated. I've tried traceback() and various debugging ideas to no avail (most likely due to my inexperience with these tools.) Here's what I have. Nk <- function(m, C) { if (length(m) > 1) { rho <- C[1, -1]

Hi Quentin, Sorry for the delay, I've been bogged down with other things today. On 14 July 2015 at 18:48, Quentin Colombet <qcolombet at apple.com> wrote: >> >> * A rematerializable interval once split is no longer rematerializable * >> >> The isRematerializable check in CalcSpillWeights.cpp uses the target >> instruction info to check that the machine

Hi, I'm slowly working through Tsay's "Analysis of Financial Time Series" 3rd ed. ?I'm trying to replicate Table 2.1 on p.47, which gives PACF, AIC, and BIC for the monthly simple returns of the CRSP value-weighted index. The data: http://faculty.chicagobooth.edu/ruey.tsay/teaching/fts3/m-ibm3dx2608.txt > da <-

Unfortunately it is a bit more complex, and the truth is less complementary to us than what you write. Reiser4's CPU usage has come down a lot, but it still consumes more CPU than V3. It should consume less, and Zam is currently working on making writes more CPU efficient. As soon as I get funding from somewhere and can stop worrying about money, I will do a complete code review, and

This is my first post to the mailing list and I guess it's a pretty stupid question but I can't figure it out. I hope this is the right forum for these kind of questions. Before I started using R I was using STATA to run a Wilcoxon signed-rank test on two variables. See data below:

XFS is the best filesystem. David Weinehall wrote: >On Tue, Mar 02, 2004 at 03:33:13PM -0700, Dax Kelson wrote: > > >>On Tue, 2004-03-02 at 09:34, Peter Nelson wrote: >> >> >>>Hans Reiser wrote: >>> >>>I'm confused as to why performing a benchmark out of cache as opposed to >>>on disk would hurt performance? >>>

Hello R users I'm using MuMIn but for some reason I'm not getting the adjusted confidence interval and uncoditional SE whe I use model.avg(). I took into consideration the steps provided by Grueber et al (2011) Multimodel inference in ecology and evolution: challenges and solutions in JEB. I created a global model to see if malaria prevalence (binomial distribution) is related to any

>> As I understand it, when you generate native code, at each landing pad >> the exception pointer appears magically in a well-known native >> register. > Well, it's not entirely magical. :-) It gets the exception object by calling > __cxa_get_exception_ptr __cxa_get_exception_ptr returns an "adjusted" pointer to the exception object, but you still have to

This is off topic and only tangentially related to statistics or R (through "HARK"ing -- Hypothesizing After Results are Known). But given the research interests of many on this list, I thought others would enjoy it. My apologies if I have overstepped (please let me know if so). Also, PLEASE DON'T RESPOND ON THIS LIST (privately is fine). This is just FYI. I don't know whether

> On 26 Jan 2016, at 15:56, Marc Schiffbauer <m at sys4.de> wrote: > > * Sami Ketola schrieb am 23.01.16 um 23:27 Uhr: >> >> >> On 23/01/16 15:33, Robert Schetterer wrote: >>> for multiple advanced imap settings at migration you might use >>> imapsync not dsync Best Regards MfG Robert Schetterer >> Sure but imapsync does not preserve

I have a puzzle as to how R is computing Cook's distance in weighted linear regression. In this case cook's distance should be given not as in OLS case by h_ii*r_i^2/(1-hii)^2 divided by k*s^2 (1) (where r is plain unadjusted residual, k is number of parameters in model, etc. ) but rather by w_ii*h_ii*r_i^2/(1-hii)^2 divided by k*s^2,