# Monthly Archives: January 2013

## Market predictions for year 2013

January 7, 2013
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Calibrations of 2013 predictions for 18 equity indices — plus some publicly available predictions. Orientation The distributions are an attempt to see the variability if there were no market-driving news for the whole year. Another way of thinking: mentally moving the distribution to center on a prediction gives a sense of the variability of results … Continue reading...

## Using the Rcpp sugar function clamp

January 7, 2013
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Since the 0.10.* release series, Rcpp contains a new sugar function clamp which can be used to limit vectors to both a minimum and maximim value. This recent StackOverflow question permitted clamp to shine. We retake some of the answers, including the ...

## Internal Consistency Reliability in R with Lambda4

January 6, 2013
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For the last year I have been developing a package “Lambda4” to improve internal consistency reliability estimation.  In the package’s conception my primary concern centered on H.G. Osburn’s maximized lambda4 estimator.  Despite a very thorough search I could not find a stats package that could utilized Osburn’s method.  I wanted to learn R and so I jumped in and...

## Internal Consistency Reliability in R with Lambda4

January 6, 2013
By

For the last year I have been developing a package “Lambda4” to improve internal consistency reliability estimation.  In the package’s conception my primary concern centered on H.G. Osburn’s maximized lambda4 estimator.  Despite a very thorough search I could not find a stats package that could utilized Osburn’s method.  I wanted to learn R and so I jumped in and...

## Demonstrating Confidence Intervals with Shiny

January 6, 2013
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For the introductory statistic student confidence intervals can seem a daunting concept to grasp.  Quite simply put it is an interval that we have a certain measure of confidence that the population parameter falls into.  The 95% confidence is the most common value chosen in my academic circle.  Nevertheless, many others may be viable as well as long as...

## Demonstrating Confidence Intervals with Shiny

January 6, 2013
By

For the introductory statistic student confidence intervals can seem a daunting concept to grasp.  Quite simply put it is an interval that we have a certain measure of confidence that the population parameter falls into.  The 95% confidence is the most common value chosen in my academic circle.  Nevertheless, many others may be viable as well as long as...

## http://cran.r-project.org/web/packages/Lambda4/index.html

January 6, 2013
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http://cran.r-project.org/web/packages/Lambda4/index.html: Our own JackStat (Tyler) published his first package in R.

## http://cran.r-project.org/web/packages/Lambda4/index.html

January 6, 2013
By

http://cran.r-project.org/web/packages/Lambda4/index.html: Our own JackStat (Tyler) published his first package in R.

## Batch forecasting in R

January 6, 2013
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I sometimes get asked about forecasting many time series automatically. Here is a recent email, for example: I have looked but cannot find any info on generating forecasts on multiple data sets in sequence. I have been using analysis services for sql server to generate fitted time series but it is too much of a black box (or I...

## Search and replace: Are you tired of nested ifelse?
It happens all the time: you have a vector of fruits and you want to replace all bananas with apples, all oranges with pineapples, and leave all the other fruits as-is, or maybe change them all to figs. The usual solution? A big old nested ifelse: ...