similar to: Automatic implementation of "trivial" constraints in optimization

Dear R-Users, my objective is to measure the overlap/divergence of two probability density functions, p1(x) and p2(x). One could apply the chi-square test or determine the potential mixture components and then compare the respective means and sigmas. But I was rather looking for a simple measure of similarity. Therefore, I used the concept of 'intrinsic discrepancy' which is defined as:

Hi, Can Someone inform me how to generate RV's using the below CDF, by inverse technique. Thanks for your help and time. My CDF is as follows \[ F(x)=0 \ \text{if} \ x < 0\]\[ F(x)=\{\frac{x-x_i}{x_{i+1}-x_{i}}*(p_{i+1}-p_{i})\}+p_{i}\ \forall \ x_{i}\leq x < x_{i+1} \] \[ F(x)=1 \ \text{if} \ x > x_{i+1} \] Regards Murthy

I think there are some missing words in "R Internals"'s description of the P_ macro. It currently has "A macro as a wrapper for ngettext", which I think ought to be something like "The macro P_ may be used as a wrapper for ngettext". The following patch also makes the 2 alternate definitions of P_ have the same argument names, StringS and StringP. Expanding the

Hi All, I have a problem to create a variable that is a function of an integral of another function. The problem is the following: I have a variable called cip. I have to create another variable called bip that is a function of the former variable cip and also the cumulative distribution function of the variable cip. Consider the equation below:

Hello, I've encountered the following: > n_500 > tau_.95 > (n*(1-tau)) [1] 25 > (n*(1-tau))<=25 [1] FALSE > (n*(1-tau))==25 [1] FALSE I'm using UNIX R Version 1.4.0, and also tested in out in Windows 1.6.0. Is this a bug? Masha

I need to refresh my memory on Probability Theory, especially on conditional probability. In particular, I want to solve the following two problems. Can somebody point me some good books on Probability Theory? Thank you! 1. Z=X+Y, where X and Y are independent random variables and their distributions are known. Now, I want to compute E(X | Z = z). 2.Suppose that I have $I \times J$ random number

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

Hi all, Sorry to bother you with the potentially not too bright question, but since I cannot get it to work, I'll have to ask someone.. I've got this vector: > token [1] sal skal skal bak b_r d_ gal kal l_r n_r pak p_r [13] sal sl_r sn_r spak sp_r st_r s_ bak d_ gal l_r pak [25] p_r sak sl_r sp_r t_ kal n_r s_ st_r sak kal

Hi R-list, I am new to optimization in R and would appreciate help on the following question. I would like to minimize the following function using two constraints: ###### fn <- function(par,H,F){ fval <- 0.5 * t(par) %*% H %*% par + F%*% par fval } # matrix H is (n by k) # matrix F is (n by 1) # par is a (n by 1) set of weights # I need two constraints: # 1.

You should be able to set PKG_FCFLAGS="-fno-stack-protector" when compiling to ensure that the stack protector is not used. (Trying that out on a Windows VM, with a simple `R CMD build` + `R CMD INSTALL`, compilation of your package succeeded but linking failed saying the DLL 'Fpi' was not found; I imagine that's a separate issue.) As an aside, be sure to check out what

Hello All, I would like to optimize a (log-)likelihood function subject to a number of linear constraints between parameters. These constraints are equality constraints of the form A%*%theta=c, ie (1,1) %*% 0.8,0.2)^t = 1 meaning that these parameters should sum to one. Moreover, there are bounds on the individual parameters, in most cases that I am considering parameters are bound between zero

Ok, I think my first mail didn't get through so I'll try this again. Please disregard. I'm trying to use subscripts on plot text. The help files say this can be done and give several example. I'm trying to do: P_{2} (for example) and so I tried: text(5,2,expression(P_{2})) which doesn't work. There are no subscript examples. I recall someone telling me that latex-like

How can I get the log odds associated with the levels in strata() within a clogit() model? I'm running R-1.9.0 on a Linux platform. I am using clogit() to run a Rasch model in Item Response Theory in psychometrics. Symbolically, the model is: logit(p_{j,k}) = \log({\Pr(p_{j,k}) \over \Pr(1-p_{j,k})}) = \theta_j - \alpha_k, That is, the log odds of answering an test item correctly is

Hi, I created a R library that uses a Fortran module. Everything works like a charm on linux. Now I'm trying to make it work on Windows. I cloned my git repository <https://github.com/ignacio82/MyPi> on a windows computer, and when I press the build and reload button on Rstudio I get these errors: ==> Rcmd.exe INSTALL --no-multiarch --with-keep.source MyPi * installing to library

Hi Arie, I understand what you're saying. The following excerpt out of the book shows that F_j does not refer exclusively to categorical factors: "...the rule does not do anything special for them, and it remains valid, in a trivial sense, whenever any of the F_j is numeric rather than categorical." Since F_j refers to both categorical and numeric variables, the behavior of

Hi Arie, Given the heuristic, in all of my examples with a missing two-factor interaction the three-factor interaction should be coded with dummy variables. In reality, it is encoded by dummy variables only when the numeric:numeric interaction is missing, and by contrasts for the other two. The heuristic does not specify separate behavior for numeric vs categorical factors (When the author of

Hi Arie, The book out of which this behavior is based does not use factor (in this section) to refer to categorical factor. I will again point to this sentence, from page 40, in the same section and referring to the behavior under question, that shows F_j is not limited to categorical factors: "Numeric variables appear in the computations as themselves, uncoded. Therefore, the rule does not

I tried to manually assign each of 3 arrays a unique TBAA node. But it does not seem to help: alias analysis still considers arrays as may-alias, which most likely prevents the desired optimization. Below is the sample code with TBAA metadata inserted. Could you please suggest what might be wrong with it? Many thanks, - D. marcusmae at M17xR4:~/forge/llvm$ opt -time-passes -enable-tbaa -tbaa

NAME xx - twice as dirty SYNOPSIS ~ > gem install "double x" require "xx" include XX::XHTML doc = xhtml_{ html_{ head_{ title_{ " go xx! " } } body_{ " one more and it would be illegal " } } } URI http://rubyforge.org/frs/?group_id=1024 DESCRIPTION xx is a library designed to extend ruby objects

Dear R-help, I am trying to express myself as best as I can here. If you also use Latex to edit math reports or other languages with similar editing method, you'll see what I'm talking about. My sincere appologies if my question is not clear enough to some extend, as also I'm not able to provide my code here because I don`t know which one I can use... When editing the title in R