similar to: What is the definition of curve continuity and smoothness

Hey, R-listers I was recommended to try using smooth.spline function for estimating 2-Dimensinal curve given a data set. So will you please tell me where to get this R function? Or which package provides this function? Thanks for your point. Fred

Hi, R-listers I tried to plot several graphs in a sigle x-y coordinate settings, like the following: |(y) s | ****** s | ***** s | sssssssssssssssssss |_______________________________(x) where "*" and "s" denote two diffrent plots. However, when I used plot(data1); % data1 is the data points of "*"

Dear R-listers, I have a dxr matrix Z, where d > r. And the product Z*Z' is a singular square matrix. The problem is how to get the left inverse U of this singular matrix Z*Z', such that U*(Z*Z') = I? Is there any to figure it out using matrix decomposition method? Thanks a lot for your help. Fred

I'm rusty, but not *that* rusty here, I hope. If W (=Z*Z' in your case) is singular, it can not have inverse, which by definition also mean that nothing multiply by it will produce the identity matrix (for otherwise it would have an inverse and thus nonsingular). The definition of a generalized inverse is something like: If A is a non-null matrix, and G satisfy AGA = A, then G is called

Hey, I want to draw several plots sequently, but have to make them dispaly in one figure. So how to achieve this? Thanks. Fred

Hey, All In principal component analysis (PCA), we want to know how many percentage the first principal component explain the total variances among the data. Assume the data matrix X is zero-meaned, and I used the following procedures: C = covriance(X) %% calculate the covariance matrix; [EVector,EValues]=eig(C) %% L = diag(EValues) %%L is a column vector with eigenvalues as the elements percent

Dear Fred, If x1 and x2 are *not* normally distributed, you can use independent component analysis (ICA) which is based on the idea that x will be "more normal" than either x1 and x2 following the central limit theorem. See package(fastICA) by JL Marchini, C Heaton, and BD Ripley for details. HTH Thomas > -----Original Message----- > From: Feng Zhang [mailto:f0z6305 at

Dear All, In the N-dimensional space, give a data point A and a curve f, how to write the explicit expression for calculating the minimal distance between A and f? Or have to use some nonlinear optimization method to calcualte it? Thanks for your point. Fred [[alternative HTML version deleted]]

Hi, I am trying to sort out a discrepancy between power calculations results between me and another statistician. I use R but I am not sure what she uses. It is on the proportions test and so I have been using pwr.prop.test. I think I have tracked the problem down to pwr.prop.test not using the continuity correction for the test (I did this by using the java applet from

Hey, all Now I am using EM algorithm to do some optimization. Within that E-step, I have to calculate some multivariate integration given some parameter values Theta and function form of a probability density function f. So I want to know if there are some package in R to do such numerical integration given such function form and parameter values? Thanks for your kind support on this. Have a

When I use wilcox.test, I get vastly different p-values than the problems from Statistics textbooks. For example: The following problem comes from "Applied Statistics and Probability for Engineers", 2nd Edition, by D. C. Montgomery. Page736, problem 14.7. The problem is to compare the sample data with a population median of 8.5. The book answer is p = 0.25, wilcox.test answer is p =

Hey, all Do you how to calculate the trigamma function, that is d**2(log(gamma(x))) / dx**2. The second-order derivative of log(Gamma(x))? I cannot find it in the R package, and somebody knows who or where to get such one? Thanks. Fred -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html

I received an assignment that I have to do in R, but I'm absolutely not very good at it. The task is the following: http://www.nabble.com/file/p22804957/question8.jpg To do this, we also get the following pieces of code (not in correct order): http://www.nabble.com/file/p22804957/hints.jpg I'm terrible at this and I'm completely stuck. The model I chose can be found in here:

Hi I am applying the wilcoxon paired signed rank test to many sub-groups of a data frame using by() and wilcox.test, and sometimes the test uses continuity correction and sometimes it doesn't. What I want to know is: 1) what is continuity correction? The docs say: correct: a logical indicating whether to apply continuity correction in the normal approximation for the p-value.

Assume F(x) is the cdf of stardard normal c.d.f, and want to get the integration of F(x)^2 over (-infinite, +infinite). So whats the value of this integration? And is there some function to achieve this? Thanks. -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info",

Hallo! Does anybody know how to calculate a sample size estimation for proportions with continuity correction? ? I only found EpiR which seems to calculate without continuity correction: library(epiR) epi.studysize(treat = .65, control = .50, n = NA, sigma = NA, power = 0.80, r = 1, conf.level = 0.95, sided.test = 2, method = "cohort") $n [1] 340 Thanks! Karl

Hello, I was using the mantelhaen.test function (2x2 J tables for conditional independence testing). I noticed that the option for the continuity correction (correction=T or correction=F) sometimes made a difference while sometimes it did give the same results regardless of correction=T or correction=F. Does the continuity correction apply only in certain cases or in certain strata with some

Hey, All Now I have a data set which is n-dimensional. And want to plot the Scatter Plot Matrix which is n by n. Does R have such function to achieve this? Thanks for your point. Fred

Summary: proc mixed vs. lme The objective of this summary is to help people to get more familiar with the specification of random effects with proc mixed or lme. Very useful are the examples of Ramon Littell's book: "SAS System for Mixed Models (1996)" (http://ftp.sas.com/samples/A55235) The same data set's are kindly made available by Douglas Bates in the

I have a question which is not necessarily related to R. I want to use a distorted political map of the world with certain countries increased in size according to a certain variable (an idea similar to the homunculi usually found in psychology textbooks) to demonstrate the coverage of particular countries in a news service. Does anyone have any idea of how to approach this? I don't think