search for: 0.033

I deal with mono-channel breathing signals sampled at 30[Hz] which are non-linear and non-stationary. My goal is to classify the signals according to common breathing patterns Trend remotion is necessary for cluster analysis but quite challenging. In fact, quasi-periodic patterns that span a number of consecutive breathing cycles should not be naively removed as they carry a lot of useful

First I would really like to thank the mailing list for help I got in the past, as a new to R I am really needing some support on hoe to code the following problem. I am trying to sort some data I have in a big file. The file has 4 columns and 19000 rows. An example of it looks like this:- G 0.892 A 0.108 G 0.883 T 0.117 T 0.5 C

OK, Let's try this again! Here is the reproducible script; it is long because I had to copy the panel dataset here. My question is related to systemfit; I don't know how to get the result for the entire panel. #Reproducible script Empdata<- read.csv("/Users/ngwinuiazenui/Documents/UPLOADemp.csv") View(Empdata) install.packages("systemfit")

Sadly you failed to set your email program to send plain text and the data is corrupted at my end. I also think you need to reduce the size of the data set... the intent here is to increase your understanding, not debug your particular analysis. I will say that I am having a very challenging time understanding what you are trying to accomplish though. What are the equations that you think need

I can't get my simultaneous equations to work using system fit. Please help. #Reproducible script Empdata<- read.csv("/Users/ngwinuiazenui/Documents/UPLOADemp.csv") View(Empdata) str(Empdata) Empdata$gnipc<-as.numeric(Empdata$gnipc) install.packages("systemfit") library("systemfit") pdata <- plm.data(Empdata,

... and the mailing list is picky about attachments... whatever you attached did not conform to the stringent requirements mentioned in the Posting Guide. Pasting the code right into the email is usually safest, though you DO have to post using plain text (as the Posting Guide indicates) or your code may get mangled by the automatic html format removal. On May 15, 2018 7:04:31 AM PDT, Bert Gunter

Hello, I have a multi-year dataset (see below) with date, a data value and a flag for the data value. I want to find the monthly median for each month in this dataset and then plot it. If anyone has suggestions they would be greatly apperciated. It should be noted that there are some dates with no values and they should be removed. Thanks Emily > print ( str(data$flow$daily) )

Unless there is good reason not to, always cc the list -- there are lots of smarter folks than I on it who can help. I may or may not have time to look at this. Hopefully someone else will. -- Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip

I want to get access to the code of an S4 method in order to possibly modify a function to accomplish my particular needs: in my case the function in is cenfit() from the package NADA Now, given my reproducible example: my.ex<-structure(list(TEC = c(0.21, 0.077, 0.06, 0.033, 0.014, 0.0072), LR = c(0L, 0L, 1L, 0L, 1L, 0L)), .Names = c("TEC", "LR"), class =

Hi, I'm trying to using pspline in bic.surv{BMA}. ############################# library(BMA) library(survival) data(veteran) test.bic.surv<- bic.surv(Surv(time,status) ~ karno+pspline(age,df=3)+diagtime+prior, data = veteran, factor.type = TRUE) summary(test.bic.surv, conditional=FALSE, digits=2) ############################# The results are:

Dear R-Helpers, I've looked high and low for a function that provides frequencies, proportions and cumulative proportions side-by-side. Below is the table I need. Is there a function that already does it? Thanks, Bob > # Generate some test scores > myValues <- c(70:95) > Score <- ( sample( myValues, size=1000, replace=TRUE) ) > head(Score) [1] 77 71 81 88 83 93 > >

Hi r-users,   I would like to extract the data that match.  Attached is my data: I'm interested in matchind the value in column 'intg' with value in column 'rand_no' > cbind(z=z,intg=dd,rand_no = rr)             z  intg rand_no    [1,]  0.00 0.000   0.001    [2,]  0.01 0.000   0.002    [3,]  0.02 0.000   0.002    [4,]  0.03 0.000   0.003    [5,]  0.04 0.000   0.003    [6,] 

Hello, When using write.table I am getting two variables pasted together (not by choice). Has anyone else had this happen? Specifically, I have the following: d _ read.dta(paste('/montecarlo/forecast/off/',F,'.dta',sep='')) write.table(d,file=paste('/montecarlo/forecast/off/csv/',F,'.csv',sep=''), row.names=FALSE, col.names=FALSE,

I have a table like the following. I want to fit Cm to Vm like this: Cm ~ Cl+Q1*b1*38.67*exp(-b1*(Vm-Vp1)*0.03867)/(1+exp(-b1*(Vm-Vp1)*0.03867))^2+Q2*b2*38.67*exp(-b2*(Vm-Vp2)*0.03867)/(1+exp(-b2*(Vm-Vp2)*0.03867))^2 I use nls, with start=list(Q1=2e-3, b1=1, Vp1=-25, Q2=3e-3, b2=1, Vp2=200). But I always get 'singlular gradient' error like this. But in SigmaPlot I can get the result. How

Full_Name: Maura Monville Version: 2.8 OS: Mac OS/X 10.5 Submission from: (NULL) (87.4.122.234) Here is the code that causes wavCWTPeaks error aats <- create.signalSeries(aa, pos=list(from=0.0, by=0.033)) aa.cwt <- wavCWT(aats) x11 (width=10,height=12) plot (aats,main=paste(insig," Cycle: ",j,sep="")) aa.maxtree <- wavCWTTree (aa.cwt,

Hi, I was wondering why the results from lm and dynlm are not the same for what I think is the same model. I have just modified example 4.2 from the Pfaff book, please see below for the code and results. Can anyone tell my what I am doing wrongly? Many thanks, Werner set.seed(123456) e1 <- rnorm(100) e2 <- rnorm(100) y1 <- ts(cumsum(e1)) y2 <- ts(0.6*y1 + e2) lr.reg <- lm(y2

Dear all, I am so ashamed to pollute the list with a trivial question, but it is a long time I have not used R, and I need a result in the next one or two hour... I have a table which I have loaded with read.table, and I want to make the mean of its columns. > slides <- read.table("slides.txt") > slides [1:5,] V1 V2 V3 V4 V5 V6 V7 V8 1

To the purpose of fitting a 2nd order polynomial (a + b*x + c*x^2) to the chunk of signal falling in a 17 consecutive samples window I wrote the following very crude script. Since I have no previous experience of using Least Square Fit with R I would appreciate your supervision and suggestion. I guess the returned coefficients of the oolynomial are: a = -1.3191398 b = 0.1233055 c = 0.9297401

I have a data frame, lets call it dat, with 3 columns ( mc, yr, ret) which represent market cap, year, and return. mc is a factor, mc, and ret are real numbers. I want to add a column to the data calculated as follows. For each year, I want to split the data by mc decile, then calculate the mean ret within that mc decile, and finally subtract that year's decile mean from the raw return. Then

Dear all, I have a question concerning the p-value. When running coxph I get a p-value = 0. :confused: Can this be true? Why aren?t there decimal points? Is there a way to find out the exact p-value? Here is the output: ---------------------------------------------------------------------------------------------------- Call: coxph(formula = Surv(start, stop, status) ~ Albumin_gproL, data = dial,