search for: maddala

INTRODUCTION TO THE PROBLEM I am trying to fit a distribution to a dataset. The distribution that I am currently considering is the (3-parameter) Singh-Maddala (Burr) distribution. The final model will fix the mean of the distribution to a given value and estimate the remaining parameters accordingly; however, the code provided below ignores this. For this distribution the three parameters ('a': corresponding to 'a' in the function 'ds...

INTRODUCTION TO THE PROBLEM I am trying to fit a distribution to a dataset. The distribution that I am currently considering is the (3-parameter) Singh-Maddala (Burr) distribution. The final model will fix the mean of the distribution to a given value and estimate the remaining parameters accordingly; however, the code provided below ignores this. For this distribution the three parameters ('a': corresponding to 'a' in the function 'ds...

We want to compute a pseudo R-squared for a model whose parameter estimation was based on maximum likelihood (function likfit, package geoR). I tried to compute the R2 proposed by Maddala (1983) which compare the maximized likelihood for the model without any predictor and the maximized likelihood for the model with all predictors. I got a really low value (0,01%). Did I miss something? Are there other R-squared which are more appropriate than the R2 of Maddala? : >sp05_l01...

Hi, The question is as follows: has anyone coded panel data unit root tests with R? Even the "first generation" tests (see e.g. Levin & Lin 1993; Pesaran, & Smith & Im 1996; Maddala & Wu 1999) would be sufficient for my needs. To my understanding, these are rather easy to code, but as I have taken just my first steps in coding with R, existing code would save me from a lot of trouble & time. With regards, Jukka Ruohonen University of Helsinki References: Levin...

Greetings, I am using both the lrm() {Design} and glm( , family=binomial()) to perform a a logisitic regression in R. Apart from the typical summary() methods, what other methods of diagnosing logistic regression models does R provide? i.e. plotting an 'lm' object, etc. Secondly, is there any facility to calculate the R^{2)_{L} as suggested by Menard in "Applied Logistic

Dear all, How do I make R show the R-squared (deviance explained by the model) in a logistic regression? Below is how I write my syntax. Basically I want to investigate density-dependence in parasitism of larvae. Note that in the end I perform a F-test because the dispersion factor (residual deviance / residual df) is significantly higher than 1. But how do I make R show the

Hello, 1) I am interested in performing a limited-dependent variable linear regression. By this I mean a classical linear regression, but for the case where the values of the dependent variable cannot vary from -infinity to +infinity, but are truncated and so are between two finite limits L1 and L2. Does R1.7 have this capability? If so what is (are) the relevant command(s)? 2) I am also

Could anyone tell me where can I find some examples of the applications to economics of a Markov chain? Many thanks in advance. Luis Rivera. -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not

Hi All, I'm new to R and am trying to run a unit root test on the vector "y" (a time series of inflation (i.e. changes in the Consumer Price Index quarter on quarter)). I've run the Augmented-Dickey-Fuller Test below (R's URCA package). It gives me an error that it cannot find the function ur.df unless I comment out the third last line of code (see below). I try to call

...dels for multiple time series rrvglm Fitting Reduced-Rank Vector Generalized Linear Models (RR-VGLMs) s Defining smooths in VGAM formulae simplex Simplex distribution sinmad Singh-Maddala Distribution Family Function skewnormal1 Univariate Skew-Normal Distribution Family Function smartpred Smart Prediction snorm Skew-Normal Distribution sratio Ordinal Regression with Stopping Ratios studentt...