similar to: SystemFit

Hi, I am trying to run many different regressions using a FOR Loop. The input data that is read into R has the following variables · Volume · Price1 · Price2 · Price3 · Price4 · Price5 · Trend · Seasonality I want to run 5 regressions, with the Volume as an dependent variable and Price, Trend & Seasonality as

I have two files with dates and prices in each. The number of rows in each of them will differ. How do I create a new file which contains data from both these files? Cbind and merge are not helpful. For cbind because the rows are not the same replication occurs. Also if I have similar data how do I write a vlookup kind of function? I am giving an example below: Say Price1 file contains the

This is my code i don't understand the error message: library(rgenoud) rm(list=ls()) set.seed(666) ######################################################### # As a first step, it is assumed that all input parameters are independent of ageing : ######################################################### InputDim <-20 # Max number of ageings in the inputs CPIRate <- rep(0.02 , InputDim ) #

Hi, I am trying to use method `validates_presence_of'' for validating my input fields on form . I m using it in my action class as follows:- ======================= validates_presence_of(params[:product][:quantity]) ====================== But when I am running my application i m getting error like:- ========================= undefined method `validates_presence_of'' for

I would like to create a subtotal table with custom bands. seq1 = seq(0, 100, by = 5) seq2 = seq(100, 1000, by = 100) Bands = c(seq1, seq2) #Prices Prices = sample(1:1000, 200, replace=F) #corresponding size for the given price above. size = sample(1:1000, 200, replace=F) How would I find the subtotal of the size based on a given price falls within a band? -- View this message in

Hi everyone: I did a search over the internet and still couldn't find answer to my problem. I have a series of prices that I'm trying to clean up by removing any prices greater than 3 times the standard deviations. So, say that prices are: price1 2010-06-18 08:00:06.916 2730 2010-06-18 08:00:07.005 2730 2010-06-18 08:00:07.005 2729 2010-06-18 08:00:07.451

The 'systemfit' function in systemfit 0.7-3 CRAN package seems to have a problem with formulas that contain transformed (eg. log) variables. If I have my data in a data frame, apparently systemfit doesn't "pass" the information of where the variables should be taken to the transforming function. I'm not entirely sure if this is a bug or just a limitation, I was just

I've been working on a new package and I have a few questions regarding the behaviour of the nlm function. I've been (for better or worse) using the nlm function to fit a linear model without suppling the hessian or gradient attributes in the objective function. I'm curious as to why the nlm requires 31 iterations (for the linear model), and then it doesn't work when I try to add

I've been trying to figure out how to get the names of the parameter vector variables when inside the function that nlm calls to return the objective function value: knls <- function( theta, eqns, data, fitmethod="OLS", instr=NULL, S=NULL ) { ## print( names( theta ) ) # returns NULL ## get the values of the parameters for( i in 1:length( theta ) )

Dear R programming folks: I'm trying to finish off a package for non-linear simultaneous system estimation and I've been trying to figure out how to get the names of the parameter vector variables when inside the function that nlm calls to return the objective function value: knls <- function( theta, eqns, data, fitmethod="OLS", instr=NULL, S=NULL ) { ## print(