search for: eia018

In order to fit a probability distribution proposed by Sichel [Journal of the Royal Statistical Society. Series A (General), Vol. 137, No. 1. (1974), pp. 25-34], I need a modified Bessel function of the 2nd kind. I notice that the base package of "R" only has modified Bessel functions of the 1st and 3rd kind. Does a modified Bessel function of the 2nd kind exist anywhere? Many

I am trying to fit a rank-frequency distribution with 3 unknowns (a, b and k) to a set of data. This is my data set: y <- c(37047647,27083970,23944887,22536157,20133224, 20088720,18774883,18415648,17103717,13580739,12350767, 8682289,7496355,7248810,7022120,6396495,6262477,6005496, 5065887,4594147,2853307,2745322,454572,448397,275136,268771) and this is the fit I'm trying to do: nlsfit

Is it possible to calculate partial sums in R? I have the equation: Px = (k / x) * SUM_{from j >= x to infinity} Pj x=1,2,3,... where k is a parameter, Pj is the Poisson probability, and x is a rank. (This is for rank-frequency data.) In other words, the frequency of an entity at rank x depends on the sum of frequencies of all entities at ranks j > x. Many thanks, Andrew

Sorry if this is a naive question, but I only started using R last week. I would like to fit a distribution to data which includes a cumulative sum: P(r) = \sum^{V}_{i=r} D e^{-n/i} i^{-d} This equation is used to fit rank-frequency data: P(r) is the frequency of an entity with rank r; V is the number of unique entity types; and D, n and d are constants to be estimated. I've found out how

I am trying to fit a lognormal distribution to a set of data and test its goodness of fit with regard to predicted values. I managed to get so far: > y <- c(2,6,2,3,6,7,6,10,11,6,12,9,15,11,15,8,9,12,6,5) > library(MASS) > fitdistr(y,"lognormal",start=list(meanlog=0.1,sdlog=0.1)) meanlog sdlog 1.94810515 0.57091032 (0.12765945) (0.09034437) But I would

Could anyone tell me whether there is an R function for removing autocorrelations from a series of observations before performing a linear or nonlinear regression analysis on them? Many thanks, Andrew Wilson

Is it possible to convert a data table in "R" to an octave scale (as done, for example, in the MVSP multivariate stats program)? I work with tables of word or category frequencies across a number of texts or text segments, e.g.: Token sect_1 sect_2 sect_3 sect_4 sect_5 sect_6 sect_7 sect_8 sect_9 sect_10 sect_11 sect_12 sect_13 sect_14 sect_15 sect_16 sect_17 sect_18 sect_19 sect_20