similar to: Optimization in R similar to MS Excel Solver

Dear R- helpers Following a draft structure of the R script for which I am facing problem Step 1 x <- of type array with original values y <- of type array with original values Step 2 for (ctr in 1:10) { # my problem here the both x and y still show the original values from step 1 # in spite of making changes to the old values of the arrays x and y in the function function

Hi , I am trying to get some estimator based on lognormal distribution when we have left,interval, and right censored data. Since, there is now avalible pakage in R can help me in this, I had to write my own code using Newton Raphson method which requires first and second derivative of log likelihood but my problem after runing the code is the estimators were too high. with this email ,I provide

Deepayan: Sorry for the additional email, but I'm concerned that I wasn't being clear. In the end, I would like a graphic that portrays my y-values on a log scale in their native data range. That is to say, I would prefer to see the axis labels as 1000 rather than 3 (log10 of 1000). Thank you for your kind assistance, Hobie Perry St. Paul, MN Hobie Perry <hobie_perry@yahoo.com>

Hi, In another thread ("PBSmapping and shapefiles") I asked for an easy way to read "shapefiles" and transform them in data that PBSmapping could use. One person is exploring some ways of doing this, but it is possible I'll have to do this "manually". With package "maptools" I am able to extract the information I need from a shapefile but it is

Hi, Is there a way, preferably with R, to read shapefiles and transform them in a format that I could then use with package PBSmapping? I have been able to read such files into R with maptools' read.shape and plot it with plot.Map, but I'd like to bring the data to PBSmapping and plot from there. I also looked at the package shapefile, but it does not seem to do what I want

--------------------------------------------------------------------------- Backport of the following patch from development: # User Ian Campbell <[hidden email]> # Date 1309968705 -3600 # Node ID e4781aedf817c5ab36f6f3077e44c43c566a2812 # Parent 700d0f03d50aa6619d313c1ff6aea7fd429d28a7 libxl: attempt to cleanup tapdisk processes on disk backend destroy. This patch properly terminates the

Dear R Community, I hope you might be able to assist with a small problem creating a function. I am working with water-quality data sets that contain the concentration of many different elements in water samples. I need to assign quality-control flags to values that fall into various concentration ranges. Rather than a web of nested if statements, I am employing the findInterval function to

What's up fellows... I am a begginer in R and i am trying to find the parameters of one likelihood function, but when i otimize it, always appers a error or advertisement and the solve does not occur. The problem seems like that: "lMix<-function(pars,y){ beta1<-pars[1] beta2<-pars[2] beta3<-pars[3] beta4<-pars[4] beta5<-pars[5] alfa1<-pars[6]

Hi there, I have following equations to be solved for a and b: a/(a+b) = x1 ab/((a+b)^2 (a+b+1)) = x2 Is there any direct function available to solve them without disentangling them manually? Thanks for your help.

Dear All, In the moment i'm using the map and maptools package to read shapefiles and display the maps. I'm looking for the possibility to draw points (randomly positioned or positioned according to a grid) into the polygons instead of filling the polygons with colors. For example: a map (shapefile) with 10 countries, 15 points in the polygon of country A, 20 points in the

We would like to fit parameters using a simulation with stochastic processes as theoretical values. We generate a simple exemple with nls.lm to see the logic and the problem: First without stochasticity (it is a dummy example, the fited value is simple the mean of a set of 10 numbers): #Ten numbers x <- 1:10 #Generate 10 Gaussian random number with mean=3 sd=1 simy <- rnorm(length(x),

I don't find how to do what I need to do in Dalgaard or 'R Cookbook', so I'm asking here. I have a data frame with water chemistry data and I want to start exploring these data. There are three factors (site, date, chemical) associated with each measurement. The data frame looks like this: > summary(chemdata) site_id.sample_date.param.quant

#is there a way to get NA in the table of descriptive statistics instead of the function stopping Thank you in advance #data x.f <- structure(list(Site = structure(c(9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L), .Label = c("BC", "HC", "RM119", "RM148", "RM179", "RM185",

Hello I am analysing aboveground biomass data from revegetation testplots which I constructed in a split-plot design using the function lme. For the experiment, the three factors are amelioration (2 levels), fertilizer (2 levels) and treatment (7 levels). Each testplot (block) has a singlereplicate of each treatment (total of 8 testplots). The blocks were constructed of topsoil. Each block was

Hello, This patch series adds an initial implementation of restriper (it''s a clever name for relocation framework that allows to do selective profile changing and selective balancing with some goodies like pausing/resuming and reporting progress to the user. Profile changing is global (per-FS) so far, per-subvolume profiles require some discussion and can be implemented in future.

In converting some older code: ## builds an OWIN to generate a set of points on a grid within the OWIN object: bdry <- read.shape( "../../data/boundary.shp" ) outline.verts <- bdry$Shapes[[2]]$verts[1:bdry$Shapes[[2]]$Pstart[2],] outline.order <- nrow( outline.verts ) : 2 bdry.poly <- vector( 2, mode="list" ) bdry.poly[[1]] <- list(

Hello, I would like to perform an NMDS on the following: I have two independent variables, which are sites and treatments. I have 6 sites which are peatlands. I collected 5 replicates (at the same time) from each of the sites. I used each of the replicates in a treatment. There were 4 treatments. 2 were controls and the other two were a simulated 30 day drought and a simulated 60 day drought.

Fellow R users, I'm using the BCE {BCE} function to run a Bayesian sediment mixing model. The aim is to find the optimum % contribution from each of the 4 source areas that can yield the target geochemistry. I have geochemistry for 4 source areas called Rat: Rat<-read.table(text="CaO MgO Na2O Al2O3 Topsoils 2.511250 0.7445500 0.7085500 14.10375 ChannelBanks

Hi all, I hope that i've posted this in the correct place. if not, please accept my apologies (where should this go?) I have carried out experimental removal of bivalves at 2 intertidal shores. Bivalves were removed by raking of surface sediments. I wish compare the biomass values of for a total of 8 species between the 2 shores My 3 treatments are: Undisturbed Controls (Cont), Procedural

Hi all, Here''s a work in progress series whcih does a partial revert of the previous swiotlb changes, and does a partial replacement with Becky Bruce''s series. The most important difference is Becky''s use of phys_addr_t rather than page+offset to represent arbitrary pages. This turns out to be simpler. I didn''t replicate the map_single_page changes, since