similar to: combine unadjusted and adjusted forest plots

# 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,

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

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,

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 <-

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:

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

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 =

To All How does one get a list of functions from a loaded package so that one can then get the appropriate help for each of the functions. Currently my method is based on a lot of trial-and-error. Here's an example of what I mean... >From this forum I learn that an interesting package called "multtest" exists on Bioconductor. I then use R Console's "Packages" --

A colleague was asking me if R does multi-level modelling as opposed to multiple regression. Since I have no knowledge of multi-level modelling (except 5 minutes googling ) I thought that I would as here. Does are offer any multi-level modeling packages? It looked like arm might be one but I was not sure. Thanks

One thing to watch out for is adjustments: - if the data is not adjusted for dividends and splits then you may be able to just download data since your last download yourself but depending on what you want to do with the data you may get misleading results. For example, if the stock trades at $100 and there is a 2 for 1 split then the next day there will be twice as many shares with each share

Hi, R users, What may be the best function in R to do variable selection in logistic regression? I have the same number of variables as the number of samples, and I want to select the best variablesfor prediction. Is there any function doing forward selection followed by backward elimination in stepwise logistic regression? Thanks, Annie [[alternative HTML version deleted]]

I downloaded Xen 3.0.1 and created an RHEL4_u3 domain on it. I need to port our application to virtualization environments like Xen and I found that our application specifically supports kernel version 2.6.9-* while I am using 2.6.16-xenU. Is there a version of Xen available with 2.6.9-* Xen Kernel? _______________________________________________ Xen-users mailing list

Dear friends - We have 25 rats, 14 of these subjected to partial removal of kidney tissue, 11 to sham operation, and then followed for 6 weeks. So far we have data on 26 urine metabolites measured by NMR 7 times during the observation. I have smoothed the measurements by b.splines in fda including a roughness penalty, and inspecting the mean curves for nephrectomized and sham animals indicate

This is a follow-up to the thread ending with: http://rubyforge.org/pipermail/vpim-talk/2008/000120.html I too am in search of some ruby parser for icalendar which properly handles timezones on the datetimes in the icalendar RFC. As I understand it there are actually three types of times. 1) UTC times with a string form of yyyymmddThhmmssZ note the trailing Z indicates zulu time aka utc. 2)

I have read the R manual and help archives, sorry but I'm still stuck. How would I do a t-test with an adjusted p-value? Suppose that I use t.test ( ) , with the function argument alternative = "two.sided", and data such that degrees of freedom = 20. The function calculates a t-statistic of 2.086, and p-value =0.05 How do I then adjust the p-value? My thought is to do

I''m not sure I''m understanding this correctly. I have a user model that is for all of my user accounts. Each user account has a time zone. I added this line to automatically create a TimeZone object for that user using their timezone: composed_of :tz, :class_name => ''TimeZone'', :mapping => %w(time_zone name) I also changed my environment.rb to

Dear friends. I wanted to reproduce a sheet of paper useful for plotting the reciprocal of some biochemical variable (creatinine) over time (Bleyer Am J Kidney Dis 34:576-578,1999). Time on X axis with units years and months. On Y axis, 1/creatinine, but with the original creatinine value indicated - to make it easier for people to use it. When using the graph, the linear decrease in 1/crea over

Hi, I'm trying to teach myself R, and by the way, re-learning statistics using Crawley's "Statistics: an introduction using R". I've reached the regression chapter, and when it deals with non-linear regresion using the nls library I face the following problem: I follow the steps--- >deer<-read.table("c:\\temp\\jaws.txt",header=T) ---data available at