similar to: Nelson- Siegel - (Yield Curve - Smoothening of curve)

Hola a todos: En la estimación de parametros de Nelson-Siegel vienen definidos 3 argumentos: rate, maturity y MidTau. Este último lo define como un vector el cual indica el término medio del vencimiento para maximizar el factor beta2.Si yo tengo un vector de maturity de 77 datos, la pregunta es:¿Qué tan importante es el argumento MidTau, y qué otra especificación tiene? no me queda muy claro cómo

Hi! Unfortunately the version loaded on the office server is 2.6.0 (for some undisclosed so called policy decision by my adamant IT dept. who are not willing to upgrade), I need to use YieldCurve package compatible with this version. On my standalone machine I have R 2.9 loaded and hence I have no problem in using the YieldCurve package. (a) Kindly guide how do I download the version of

I am using speex for encoding and decoding speech files in a speech synthesis program. I am using concatenative approach for speech synthesis using diphones (small speech chunks) as basic unit. Now in my application, the order of diphones to be joined after decoding is determined at runtime. Therefore I have to encode each diphone independent of others. I find out that when I encode diphones

Hello, I'm new to this list. Sorry if my question or parts of it already came up before. For my research in geostatistics, I am working with large sets of data in R (basically large matrices containing discrete x and y coordinates and a value for a certain parameter). These sets are obtained by kriging. The operation I'd like to perform is smoothen the output data set. I want to do it by

Hi I'm trying to use ggplot2 to chart a dataset that I've drawn in from excel.? When I run the qplot command, I get the following error message: Error: ggplot2 doesn't know how to deal with data of class character It feels like I need to coerce one of the fields in my data frame. Here's the code, which is short: #draw data in from network location

Hi everybody! Can anybody help me to find an R-function for the Siegel-Tukey test. Than you in advance. Ralf Finne SYH, University of Applied Sciences Vasa Finland

Hello R friends, I am looking for a function to perform the Siegel-Tukey test in R. Can anyvbody help me? Thanks so much! J. Hedderich -- --------------------------------------------------------------- Dipl. Inform. J. Hedderich Institut f??r Medizinische Informatik und Statistik im Klinikum S.H. - Campus Kiel - Phone : 0431/5973182 Brunswiker Str.

Hello, With which package can I build a yield curve using swap data with the bootstrapping method? Thanks for the reaction, André [[alternative HTML version deleted]]

Hi, Would anyone know if it is possible to run a Beveridge Nelson decomposition of a univariate time series object in R? I searched in the help files but didn't come across any potential methods. Thanks very much, Shruthi -- View this message in context: http://www.nabble.com/Beveridge-Nelson-Decomposition-tp21789452p21789452.html Sent from the R help mailing list archive at Nabble.com.

Dear useRs, I'm trying to estimate the proportion of individuals with a without a certain recurring ailment at several times points. The data are of the survival type, with "start"-"stop" dates and whether the individual had the ailment in that interval. Some cases are observed until database closure and some died or are lost to followup. The interest is not on death. I

Hi, I am taking a survival class. Recently I need to do the Nelson-Aalen estimtor in R. I searched through the R help manual and internet, but could not find such a R function. I tried another way by calculating the Kaplan-Meier estimator and take -log(S). However, the function only provides the summary of KM estimator but no estimated values. Could you please help me with this? I would

Hi, I am computing the Nelson-Aalen (NA) estimate of baseline cumulative hazard in two different ways using the "survival" package. I am expecting that they should be identical. However, they are not. Their difference is a monotonically increasing with time. This difference is probably not large to make any impact in the application, but is annoyingly non-trivial for me to just

Hard to tell from the info you are giving us. I assume this regards the "mice" package? One way to proceed is to set options(error=recover) which will dump you into the browser() environment when the error occurs and you can oka around and see what the value of variables was at the point of the error. This could give you a clue about what is going on. -pd > On 22 May 2018, at 15:29

Dear all, Currently, I am doing a research project about serum sodium levels and falling. I am doing my analysis in R. I am performing the multiple imputation right now. I want to perform a survival analysis later, but therefore I need to specify the Nelson-Aalen estimator. My dataset is called DF1, the event indicator is Falls and the time variable is Time. The code that I use is as follows:

Hi, I recently ran into the problem that I needed a Siegel-Tukey test for equal variability based on ranks. Maybe there is a package that has it implemented, but I could not find it. So I programmed an R function to do it. The Siegel-Tukey test requires to recode the ranks so that they express variability rather than ascending order. This is essentially what the code further below does. After the

Hi, I've been trying to recreate plots of that follow a cubic form. The the original graphs I'm looking at were produced with specialized software (Delta Graph), and although I can reproduce it almost exactly with R, the only difference is in the actual display of the curves I've plotted. I've noticed that in R all curves are pixelated, regardless of howmany points I use. Is

Hello, I am trying to fit my histogram to a smooth Gaussian curve(the data closely resembles one except a few bars). This is my code : #!/usr/bin/Rscript out_file = "irc_20M_opencl_test.png" png(out_file) scan("my.csv") -> myvals hist(myvals, breaks = 50, main = "My Distribution",xlab = "My Values") pdens <- density(myvals, na.rm=T) plot(pdens,

R Friends, I have data from which I would like to learn a more general (smoothened) trend by applying data smoothing methods. Data points follow a positive stepwise function. | x x | xxxxxxxx xxxxxxxx | x x |xxxx xxx xxxx | xxxxxxxxxxxxxxxxx | |

Hi, In continuation of the discussion of melange comments,about negative value returned in matcher due to logarithm of probabilities. *I**f we make K suitably large, we could clamp each log(K.Pi) to be >= 0, and this change will only affect really low probability terms (those with Pi < 1/K, so you can adjust K to suit):* *W' = sum(i=1,...,n, max(log(K.Pi), 0))* Did you mean for low

Am Fr, Feb 18, 2005 at 09:55:43 -0300 schrieb Manoel Pinho: > Did you see these articles: > > http://linux.slashdot.org/article.pl?sid=05/02/17/1318212&tid=125&tid=109&tid=106 > > and > > http://www.microsoft-watch.com/article2/0,1995,1766738,00.asp > > ? > > M$ sucks !! > > This would break any efforts like your winetools... Yes, I read