similar to: Correct statistical inference for linear regression models without intercept in R

man for `qr` says that the function uses LINPACK's DQRDC, while it in fact uses DQRDC2. ``` The QR decomposition of the matrix as computed by LINPACK or LAPACK. The components in the returned value correspond directly to the values returned by DQRDC/DGEQP3/ZGEQP3 ```

Dear Community, say, I have an annual ts() object sampled from 1960 to 1969 like: ta<-ts(1:10, start=1960, frequency=1) How can I extract the value from the year 1965? I mean, not by: ta[6] but by something like: ta[1965] where I'm directly referring to the year of the observation? Thank you in advance! -- View this message in context:

Hallo! I lese gro?e Zeitreihen in R ein z.B. mit: > disc<-read.table("F:/R/DATA/discount_rate_usa.txt") disc hat dann folgende Struktur: > disc[1:5] V1 V2 1 01/03/1955 1.5 2 01/04/1955 1.5 3 01/05/1955 1.5 4 01/06/1955 1.5 5 01/07/1955 1.5 ich will das disc als Zeitreihe erkannt wird und will z.B 01/03/1955 in ein Datum verwandeln, aber es wird als

Could somebody recommend some good nonparametric statistical inference textbooks for a beginner? And what are pros and cons of each book? Nonparametric statistical methods by Hollander seems to be more difficult for a beginner, but is great as a reference, right? Are there any books that are easier to learn than Hollander's? Also, I see some books in the wiki page. I don't find the

Dear R users, we proudly announce the latest release of our R package plsdof: Degrees of Freedom and Statistical Inference for Partial Least Squares. Features include: * Degrees of Freedom estimates for Partial Least Squares (PLS) Regression * Model selection for PLS based on various information criteria and on cross-validation * approximate confidence intervals and significance tests for PLS

Dear R users, we proudly announce the latest release of our R package plsdof: Degrees of Freedom and Statistical Inference for Partial Least Squares. Features include: * Degrees of Freedom estimates for Partial Least Squares (PLS) Regression * Model selection for PLS based on various information criteria and on cross-validation * approximate confidence intervals and significance tests for PLS

Dear R help list, I am modeling some survival data with coxph and survreg (dist='weibull') using package survival. I have 2 problems: 1) I do not understand how to interpret the regression coefficients in the survreg output and it is not clear, for me, from ?survreg.objects how to. Here is an example of the codes that points out my problem: - data is stc1 - the factor is dichotomous

Dear all I am a BEGINNER and have R on my Mac. I saved my excel file as .txt file, I have just one column with first row as the column name. My file when read by R looks like this. After reading the table I try to make a histogram by hist(dbh), it says object dbh not found. What am I doing wrong? thanks dbh 1 11.53 2 16.05 3 7.36 4 16.05 5 8.66 6 12.74 7 22.93 8 7.55 9

1. The weibull is the only distribution that can be written in both a proportional hazazrds for and an accelerated failure time form. Survreg uses the latter. In an ACF model, we model the time to failure. Positive coefficients are good (longer time to death). In a PH model, we model the death rate. Positive coefficients are bad (higher death rate). You are not the first to be confused

Thanks for sharing the questions and responses! Is it possible to appreciate how much the coefficients matter in one or the other model? Say, using Biau's example, using coxph, as.factor(grade2 == "high")TRUE gives hazard ratio 1.27 (rounded). As clinician I can grasp this HR as 27% relative increase. I can relate with other published results. With survreg the Weibull model gives a

Hi all, Following up on Holger's email last week: Does anyone know if there exists a library that implements the sensitivity tests for hidden bias for matched pairs and unmatched groups as proposed in Rosenbaum's Observational Studies (2002: ch.4)? Thanks. Best, jens

#Conditional inference forest ("Party" package) error message states that levels in factors of new data do not match original data, but they do... #create conditional inference forest oc_listed.fit1 <- cforest(Listed~ HabMode,controls=cforest_unbiased(ntree=500), data=oc.complete) #use predict function for subset of data #this works correctly

Computational Aspects of Simulation and Inference for Stochastic Processes and the YUIMA Project This two-day workshop is aimed at presenting the latest results on simulation and inference for stochastic processes and their current and prospect implementation within the YUIMA R package. Dates: March 27 (Tue) 9:15-12:15, 14:45-17:45 March 28 (Wed) 9:15-12:15, 14:45-17:45 Location:

Hi Guys! I'm Praveen Velliengiri, studying third year Msc Data Science at PSG COLLEGE OF TECHNOLOGY. I would like to participate in GSoC 2018 under LLVM Organization. I went through the GSoC Project ideas page and the LLVM mailing list. I really liked the *FUNCTION ATTRIBUTE INFERENCE *project. I'm starting to make initial studies for the project. I'm new to LLVM i don't know

Hello all ! As you (Nuno Lopes) suggested I went through the basics of interprocedural analysis. I'm new to LLVM and Compilers in general. I have looked llvm/lib/Transforms/IPO/FuntionAttrs.cpp and InferFunctionAttrs.cpp. As I'm new to compiler technology I find difficult to come up with new ideas with respect to function attributes. I would love to hear any additional resources like

Christopher Lamb wrote: > A strategy that we have had luck with in the past is the concept of a > "vector boolean" type, which is the result of a comparison between two > vectors. It's then necessary to perform a reduction (and, or) on the > elements in order to produce a scalar boolean value that's suitable for > a branch. This also allows stuff like letting

On Apr 23, 2007, at 5:06 PM, Chris Lattner wrote: > On Sun, 22 Apr 2007, Christopher Lamb wrote: >> I have a back end which has both scalar and vector registers that >> alias each other. I'm having a problem generating the ISel from >> tablegen that appears only when a vector register class is declared >> to contain integer vectors. At that moment tablegen

Can someone explain why TableGen can't figure this out? VCVTDQ2PS128rm: (set:isVoid VR128:v4f32:$dst, (sint_to_fp:v4f32 (bitconvert:isInt (ld:v4i32 addr:iPTR:$src)<<P:Predicate_memop>>))) llvm/tblgen: In VCVTDQ2PS128rm: Could not infer all types in pattern! The pattern as written looks like this: [(set VR128:$dst, (v4f32 (sint_to_fp (bc_memopv4i32 addr:$src))))] I'm

How is bc_memopv4i32 defined? The bitconvert in the tablegen output is marked isInt, which means it's the node that didn't get inferred. Dan On Jun 4, 2009, at 1:06 PM, David Greene wrote: > Can someone explain why TableGen can't figure this out? > > VCVTDQ2PS128rm: (set:isVoid VR128:v4f32:$dst, (sint_to_fp:v4f32 > (bitconvert:isInt (ld:v4i32

On Friday 05 June 2009 17:41, Dan Gohman wrote: > How is bc_memopv4i32 defined? The bitconvert in the tablegen > output is marked isInt, which means it's the node that didn't get > inferred. def bc_memopv4i32 : PatFrag<(ops node:$ptr), (bitconvert (memopv4i32 node:$ptr))>; -Dave