similar to: MODWT exceeds sample size

Airon, I don't think you have to find an English computer 'cause the following must work in your Chinese one :-) Let me explain. First of all, change your lines to xdata <- ckhdat$Adj..Close[1:1447] #names(ckhdwt.la8) <- c("w1", "w2", "w3", "w4", "w5","w6", "v6") note the # sign, i.e., DO NOT change the names

Dear R Users, For running wavelet functions using dwt( ), modwt( ), and mra( ), a wavelet filter algorithm is applied. For all these functions, default is "la8" and other possibility is "haar". In related documents, another possibilities like as symlet and coiflet ... are not cited. Besides "la8" and "haar", which wavelet filters can be used? Thank

Airon, I used R2.4.0 on a Windows XP (SP2) (not Chinese :-)) and it still works: > data = read.csv("u:/airon.csv") > xdata = data$Adj..Close > modwt.la8 = modwt(xdata, "la8", n.level=6) > summary(modwt.la8) Length Class Mode d1 1467 -none- numeric d2 1467 -none- numeric d3 1467 -none- numeric d4 1467 -none- numeric d5 1467 -none- numeric d6 1467

Hi: I have encountered problems with imodwt and universal.thresh.modwt and cannot find any reference in R Search. Hope someone can give me some ideas: Starting with modwt.la8 <- modwt(xdata, "la8", n.level=6) <-- this seems to work fine (1) ydata <- imodwt(modwt.la8) will always give ydata as numeric(0) (no values) instead of being a time series data with

I take the liberty of pasting the on-line documentation for package "wavelets", functions "dwt" and "wt.filter", pertinent to the wavelet/filter choice. While I apologize for my verbose messages with huge attachments, I encourage whoever loads packages to CRAN to take some minutes to reread the attached documentation. Usage dwt(X, filter="la8", n.levels,

Hi everyone I am using the wavelet and waveslim package in R to find the wave variance.Here is the code return.modwt<-modwt(X, filter="la8", n.levels=5, boundary="periodic", fast=TRUE) return.modwt.var<- wave.variance(return.modwt, type="nongaussian") Where X is a uni-variate time series. I am expecting a matrix with 5 rows(no. of levels) and 3

Dear all: Greetings from Mumbai, India. Reference?R help solution [Rogerio, Thu 16 Nov 2006 - 20:54:25 GMT]. Simonsen, Jensen and Johansen (2002) [arXiv:cond-mat/0202352v1] note "(.wavelet filtered was...) achieved?by first transforming the log-price [...] to the?wavelet-domain, setting all wavelet coefficient corresponding?to scales larger then 1000 trading days to zero, and finally

Airon, I'm not sure I have understood your question. Anyway, it seems to me that you'll have to code a little. Take a look at ?modwt. I think you'll have to put zeros each scale a time except the one you want to reconstruct. Then do imodwt. After some small loop, I think you'll get the desired result. HTH, Rogerio. ---------- Cabe?alho original ----------- De: "Airon

Hai I'm Dee. I'm trying to write var data from these codes inside excel file. My directory to store the data is *D:\FYP\image* . these are my codes, can you help give an advice or idea with my problem: l*ibrary("biOps") library("waveslim") library("xlsReadWrite") x <- readTiff("D:\\FYP\\image\\SignatureImage\\user186g1.tif") y <-

Hai, I'm trying to write these var output data from these codes inside excel file. My directory to store the data is /D:\FYP\image / but receive an error message : /Error in write.xls(mydata, "D:\\FYP\\image.mydata.xls") : object 'mydata' not found/ these are my codes, can you help give an advice or idea with my problem: /library("biOps")

Hi there, When I run the code below I get the error Error in xy.coords(x, NULL, log = log) :(list) object cannot be coerced to type 'double' Any tips how I can resolve this? > > library("waveslim") > > vols=read.csv(file="C:/Users/ocuk/My Documents/Abs Vol.csv", header=TRUE, > sep=",") > x<-c(vols[,1]) > #x > #data(ibm) >

Given a time series of length N, I am trying to figure out its maximum DWT decomposition level. With reference to "dwt" function of R package "wavelets", running the provided example I get the following and wonder how the maximum decomposition level (which is not an integer number) is calculated. I tried myself the formula in the on-line documentation but could not get the

I have written a short script to estimate the size of a test of non-constant mean in an AR(1) time series. When I run the simulation on my PC (R version 2.7.1), I get the expected result: an empirical size much larger than the nominal size. On the Red Hat machine (R version 2.7.2) in my department, however, I get p-values > .45 for every simulated test. Below is my simulation code (uses

hi everyone . I am trying to use some packages but there are some functions have the same name in different package. for example dwt function both in packages wavelets and waveslim dwt(X, filter="la8", n.levels, boundary="periodic") How can I avoid mixing them up ? -- TANG Jie Email: totangjie@gmail.com Tel: 0086-2154896104 Shanghai Typhoon Institute,China

I would like to create a vector of pairlist (flag, binary_value) like: (variable ="TrendOff", value = 0) (variable ="MOdwt", value = 1) (variable ? "ZeroPadding", value =1) ................................................ I tried the following syntax but the emcompassing list (that I called "flags") is not made up of pairlists. Instead it

--gKMricLos+KVdGMg Content-Type: text/plain; charset=us-ascii Content-Disposition: inline I compiled R 2.3.1 on two SuSE systems. With SuSE 8.2 I got an error which I had not on SuSE 10: /usr/lib/gcc-lib/i486-suse-linux/3.3/../../../../i486-suse-linux/bin/ld: cannot find -lRlapack On both system libRlapack.so is made, but the size is verz different: SuSE 8.2: -rwxr-x--- 1 wf sys

R gurus: I'm trying to get another round of rconifers out and I need some advice/help crushing differences in the examples test. I'm trying to make sure the max sdi values are being respected. I've added a tests/rconifers-Ex.Rout.save (from windows i386-pc-mingw32) and when I ran R CMD check (both R-2.13.0), I got the following results: * using log directory

Hi Max, > The Glasgow Haskell Compiler LLVM backend is generating a lot of code which > appears to be optimised by LLVM quite poorly. The problem is demonstrated by > this C source code: if I run this at -O3 under llvm-gcc from top-of-tree on x86-64 linux then (1) it computes that g(5) is equal to 95, and main is transformed to just print 95. (2) g is transformed into code with no

Hello, I am trying to create a plot often seen in hydrodynamic work than includes a contour plot representing the water speed with arrows pointing in the direction of flow. Does anyone have any idea how I might add arrows based on wf$angle (in the example below) to the plot below? Thanks in advance! Sam library(lattice) speed <- runif(100, 0, 20) wf <- data.frame(speed) wf$width <-

Hi, The Glasgow Haskell Compiler LLVM backend is generating a lot of code which appears to be optimised by LLVM quite poorly. The problem is demonstrated by this C source code: int wf(int sp[]) { if (sp[0] == 0) { return sp[2] + sp[3]; } else { sp[3] = sp[3] + (sp[1] * 5); sp[2] = (sp[2] + sp[0]) + 1; sp[1] = sp[1] - 1; sp[0] = sp[0] - 1;