search for: systol

...xxx => { > > > > This looks like a dialplan pattern match exten but you do not have a > > leading '_' to indicate > > that it is a pattern so this exten will only match a literal > "1619xxxxxxx". > > > > Answer(); > > Playback(welcomesystole); > > Read(digito1,,3); > > Playback(diastole); > > Read(digito2,,3); > > > > Agi(agi:// > 10.10.22.171:4573/hello.agi?systole=${digito1}&diastole=${digito2}< > http://10.10.22.171:4573/hello.agi?systole=$%7bdigito1%7d&diastole=$%7bdigito2%7d > &gt...

...hins is supposed to be. I'm assuming here (and I don't even play an expert on TV) that vertical patterns are easier to grasp than diagonal ones. Now, the main example on that web page (and in the PDF file you can get to from the URI posted in the original message) can be summarised as Systolic >= 180 BIG Systolic 160..179 moderate Everything else pretty much small which is quite easy to see if "systolic" is the horizontal or vertical axis, but when the vertical axis is "systolic + diastolic" and the horizontal is "diastolic - systolic" (a bit of...

...n { > 1619xxxxxxx => { > This looks like a dialplan pattern match exten but you do not have a leading '_' to indicate that it is a pattern so this exten will only match a literal "1619xxxxxxx". > Answer(); > Playback(welcomesystole); > Read(digito1,,3); > Playback(diastole); > Read(digito2,,3); > Agi(agi:// > 10.10.22.171:4573/hello.agi?systole=${digito1}&diastole=${digito2}); > Hangup() > } > It is up to you where yo...

...36.22222 36.5 36.66667 37.1 89 DIASTOLIC BLOOD PRESSURE 73.60079 9.4656186 50.0 67.00000 73.0 80.00000 95.0 253 HEIGHT 171.94000 9.2011670 153.5 166.50000 173.0 176.25000 190.0 20 PULSE RATE 67.48221 11.7657645 40.0 60.00000 68.0 75.00000 97.0 253 SYSTOLIC BLOOD PRESSURE 131.91700 14.4986667 97.0 122.00000 132.0 140.00000 185.0 253 WEIGHT 85.17079 17.3150434 57.3 70.90000 83.1 100.00000 122.5 89 now i want to transpose this dataset like BODY TEMPERATURE mean 36.41099 sd 0.4015699...

How do I generate a value in R from a poisson distribution with mean 20? Thanks! -- View this message in context: http://www.nabble.com/Generating-a-value-tf4922234.html#a14086120 Sent from the R help mailing list archive at Nabble.com.

...- rnorm(n, 120, 15) cholesterol <- rnorm(n, 200, 25) sex <- factor(sample(c('female','male'), n,TRUE)) label(age) <- 'Age' # label is in Hmisc label(cholesterol) <- 'Total Cholesterol' label(blood.pressure) <- 'Systolic Blood Pressure' label(sex) <- 'Sex' units(cholesterol) <- 'mg/dl' # uses units.default in Hmisc units(blood.pressure) <- 'mmHg' # Specify population model for log odds that Y=1 L <- .4*(sex=='male') + .045*(age-50) + (log(chole...

...one predictor, two predictors, and three predictors. I have not yet seen any diamond graphs with three explanatory variables... b. Figures 4-6 display (age-adjusted rate of end-stage renal disease due to any cause per 100,000 person-years) as the thing to be explained, with systolic blood pressure (measured in mm Hg) and diastolic pressure (measured in mm Hg) as the explanatory variables. Once again the explanatory variables are continuous, not categorical. They are cut to 6 levels each. With the raw data, one could perhaps get a contour plot of fitted...

Dear R People: I finally (Yay!) got R installed in a classroom! Anyhow, I have a respectful request, please: could anyone recommend some nice undergrad projects in R, please? This is in a statistical computation class; first time being run. Thanks, Erin -- Erin Hodgess Associate Professor Department of Computer and Mathematical Sciences University of Houston - Downtown mailto:

On Thu, Aug 6, 2015 at 11:56 AM, Murthy Gandikota <murthy64 at hotmail.com> wrote: > Tested with X-Lite and it worked fiine. Is there some way to replace > "Anonymous" with a config parameter? > > Thanks for your kind help > > ---------------------------------------- > > From: murthy64 at hotmail.com > > To: asterisk-users at lists.digium.com >

...$ blood.pressure <- rnorm(n, 120, 15) $ cholesterol <- rnorm(n, 200, 25) $ sex <- factor(sample(c('female','male'), n, T)) $ label(age) <- 'Age' $ label(cholesterol) <- 'Total Cholesterol' $ label(blood.pressure) <- 'Systolic Blood Pressure' $ label(sex) <- 'Sex' $ units(cholesterol) <- 'mg/dl' # uses units.default in Hmisc $ units(blood.pressure) <- 'mmHg' $ $ # Specify population model for log odds that Y=1 $ L <- .4*(sex=='male') + .045*(age-50) + +...

...> cholesterol <- rnorm(n, 200, 25) > sex <- factor(sample(c('female','male'), n,TRUE)) > label(age) <- 'Age' # label is in Hmisc > label(cholesterol) <- 'Total Cholesterol' > label(blood.pressure) <- 'Systolic Blood Pressure' > label(sex) <- 'Sex' > units(cholesterol) <- 'mg/dl' # uses units.default in Hmisc > units(blood.pressure) <- 'mmHg' > > # Specify population model for log odds that Y=1 > L <- .4*(sex=='male') + .0...

...cholesterol <- rnorm(n, 200, 25) sex <- factor(sample(c('female','male'), n,TRUE)) label(age) <- 'Age' # label is in Hmisc label(cholesterol) <- 'Total Cholesterol' label(blood.pressure) <- 'Systolic Blood Pressure' label(sex) <- 'Sex' units(cholesterol) <- 'mg/dl' # uses units.default in Hmisc units(blood.pressure) <- 'mmHg' # Specify population model for log odds that Y=1 L <- .4*(sex=='male') +...

...equally good. That's the point of the plot() method, where you can look at hundreds of best models from 30 or so variables and see which variables are in most of the good models, and which variables tend to occur together or separately -- for example, if you have two related variables such as systolic blood pressure and diastolic blood pressure do they substitute for each other or do they tend to occur in the same model. Thanks all (and again - thanks Thomas for all your patient answers so far) Tal ---------------------------------------------- My contact information: Tal Galili Phone...

...<- rnorm(n, 120, 15) cholesterol <- rnorm(n, 200, 25) sex <- factor(sample(c('female','male'), n,TRUE)) label(age) <- 'Age' # label is in Hmisc label(cholesterol) <- 'Total Cholesterol' label(blood.pressure) <- 'Systolic Blood Pressure' label(sex) <- 'Sex' units(cholesterol) <- 'mg/dl' # uses units.default in Hmisc units(blood.pressure) <- 'mmHg' # Specify population model for log odds that Y=1 L <- .4*(sex=='male') + .045*(age-50) + (log(cholest...

...cholesterol <- rnorm(n, 200, 25) sex <- factor(sample(c('female','male'), n,TRUE)) label(age) <- 'Age' # label is in Hmisc label(cholesterol) <- 'Total Cholesterol' label(blood.pressure) <- 'Systolic Blood Pressure' label(sex) <- 'Sex' units(cholesterol) <- 'mg/dl' # uses units.default in Hmisc units(blood.pressure) <- 'mmHg' # Specify population model for log odds that Y=1 L <- .4*(sex=='male') +...

Dear guRus, I would like to loop over a medium amount of Sweave code, including both R and LaTeX chunks. Is there any way to do so? As an illustration, can I create a .tex file like this using a loop within a .Rnw file, where the "1,2,3" comes from some iteration variable in R? ################################################ \documentclass{article} \usepackage{Sweave} \begin{document}

...cholesterol <- rnorm(n, 200, 25) > sex <- factor(sample(c('female','male'), n,TRUE)) > label(age) <- 'Age' # label is in Hmisc > label(cholesterol) <- 'Total Cholesterol' > label(blood.pressure) <- 'Systolic Blood Pressure' > label(sex) <- 'Sex' > units(cholesterol) <- 'mg/dl' # uses units.default in Hmisc > units(blood.pressure) <- 'mmHg' > > # Specify population model for log odds that Y=1 > L <- .4*(sex=='male'...

dear:teacher i have a problem which about the polr()(package "MASS"), if the response must have 3 or more levels? and how to fit the polr() to 2 levels? thank you. turly yours [[alternative HTML version deleted]]

...\code{\link[Hmisc]{rcspline.eval}}, \code{\link[Hmisc]{rcspline.restate}}, \code{\link{Design}}, \code{\link{cph}}, \code{\link{lrm}}, \code{\link{ols}}, \code{\link{datadist}} } \examples{ \dontrun{ options(knots=4, poly.degree=2) country <- factor(country.codes) blood.pressure <- cbind(sbp=systolic.bp, dbp=diastolic.bp) fit <- lrm(Y ~ sqrt(x1)*rcs(x2) + rcs(x3,c(5,10,15)) + lsp(x4,c(10,20)) + country + blood.pressure + poly(age,2)) # sqrt(x1) is an implicit asis variable, but limits of x1, not sqrt(x1) # are used for later plotting and effect estimation # x2 fitted with res...