# 1993 search results for "time series"

## Automatic drug utilization reports with R and ggplot2

September 18, 2012
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This program takes a data set of drug utilisation of 4 fictional drugs in 10 fictional hospitals and plots each time-series with a locally weighted regression (Lowess) trend line. It also places an time-series trend of the usage for each … Continue reading →

## Example 10.2: Custom graphic layouts

September 17, 2012
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In example 10.1 we introduced data from a CPAP machine. In brief, it's hard to tell exactly what's being recorded in the data set, but it seems to be related to the pattern of breathing. Measurements are taken five times a second, leading to on the o...

## Variability of garch estimates

September 17, 2012
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Not exactly pin-point accuracy. Previously Two related posts are: A practical introduction to garch modeling garch and long tails Experiment 1000 simulated return series were generated.  The garch(1,1) parameters were alpha=.07, beta=.925, omega=.01.  The asymptotic variance for this model is 2.  The half-life is about 138 days. The simulated series used a Student’s t distribution … Continue reading...

## The R-Podcast Episode 10: Adventures in Data Munging Part 2

September 16, 2012
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I’m happy to present episode 10 of the R-Podcast! Season 1 of the R-Podcast concludes with part 2 of my series on data munging, in which I discuss issues surrounding importing data sets contained in HTML tables. I share how I used the XML and RCurl packages to validate and import data from hockey-reference.com for

## Tutorials for Learning Visualization in R

September 12, 2012
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Today's guest post comes from Nathan Yau. Nathan runs FlowingData, a site on statistics and visualization, and is the author of Visualize This. Years ago, when I started FlowingData, the purpose of the blog was to catalog and think out loud about visualization, in its many varieties. In the beginning I was talking to myself for the most part,...

## Not fooled by randomness

September 10, 2012
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The paper is “Not Fooled by Randomness: Using Random Portfolios to Analyze Investment Funds” by Roberto Stein.  Here is an explanation of the idea of random portfolios. Favorite sentence The real question here is whether we’re actually measuring skill, or these are still measures of performance, so influenced by extraneous factors that the existence of … Continue reading...

## Implementing the CountSummary Procedure

In my last post, I described and demonstrated the CountSummary procedure to be included in the ExploringData package that I am in the process of developing.  This procedure generates a collection of graphical data summaries for a count data sequence, based on the distplot, Ord_plot, and Ord_estimate functions from the vcd package.  The distplot function generates both the Poissonness...

## Suicide statistics and the Christchurch earthquake

September 5, 2012
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Suicide is a tragic and complex problem. This week New Zealand’s Chief Coroner released its annual statistics on suicide, which come with several tables and figures. One of those figures refers to monthly suicides in the Christchurch region (where I … Continue reading →

## New Attribution Functions for PortfolioAnalytics

September 1, 2012
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Another Google Summer of Code (GSoC) project this summer focused on creating functions for doing returns-based performance attribution. I’ve always been a little puzzled about why this functionality wasn’t covered already, but I think that most analysts do this kind of work in Excel. That, of course, has its own perils. But beyond the workflow