Posts Tagged ‘ Uncategorized ’

Overview of new features in SAS/IML 12.3

July 30, 2014
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Overview of new features in SAS/IML 12.3

Unless you diligently read the "What's New" chapter for each release of SAS software, it is easy to miss new features that appear in the language. People who have been writing SAS/IML programmers for decades are sometimes surprised when I tell them about a useful new function or programming feature. […]

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Introducing people to R: 14 years and counting

July 29, 2014
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I've been introducing people to R for quite a long time now and I've been doing some reflecting today on how that process has changed quite a bit over time. I first started using R around 1998--1999 I think I … Continue reading →

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Lexicographic combinations in SAS

July 28, 2014
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Lexicographic combinations in SAS

In a previous blog post, I described how to generate combinations in SAS by using the ALLCOMB function in SAS/IML software. The ALLCOMB function in Base SAS is the equivalent function for DATA step programmers. Recall that a combination is a unique arrangement of k elements chosen from a set […]

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Student forecasting awards from the IIF

July 26, 2014
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Student forecasting awards from the IIF

At the IIF annual board meeting last month in Rotterdam, I suggested that we provide awards to the top students studying forecasting at university level around the world, to the tune of $100 plus IIF membership for a year. I’m delighted that the idea...

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Academic statisticians: there is no shame in developing statistical solutions that solve just one problem

July 25, 2014
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I think that the main distinction between academic statisticians and those calling themselves data scientists is that the latter are very much willing to invest most of their time and energy into solving specific problems by analyzing specific data sets. … Continue reading →

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Coherent population forecasting using R

July 24, 2014
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Coherent population forecasting using R

This is an example of how to use the demography package in R for stochastic population forecasting with coherent components. It is based on the papers by Hyndman and Booth (IJF 2008) and Hyndman, Booth and Yasmeen (Demography 2013). I will use Australian data from 1950 to 2009 and forecast the next 50 years. In demography, “coherent” forecasts are where male and females (or other sub-groups) do not diverge over…

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Computing prediction ellipses from a covariance matrix

July 23, 2014
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Computing prediction ellipses from a covariance matrix

In a previous blog post, I showed how to overlay a prediction ellipse on a scatter plot in SAS by using the ELLIPSE statement in PROC SGPLOT. The ELLIPSE statement draws the ellipse by using a standard technique that assumes the sample is bivariate normal. Today's article describes the technique […]

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Plotting the characteristic roots for ARIMA models

July 23, 2014
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Plotting the characteristic roots for ARIMA models

When modelling data with ARIMA models, it is sometimes useful to plot the inverse characteristic roots. The following functions will compute and plot the inverse roots for any fitted ARIMA model (including seasonal models). # Compute AR roots arroots <- function(object) { if(class(object) != "Arima" & class(object) != "ar") stop("object must be of class Arima or ar") if(class(object) == "Arima") parvec <- object$model$phi else parvec <- object$ar if(length(parvec) > 0)…

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Add a prediction ellipse to a scatter plot in SAS

July 21, 2014
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Add a prediction ellipse to a scatter plot in SAS

It is common in statistical graphics to overlay a prediction ellipse on a scatter plot. This article describes two easy ways to overlay prediction ellipses on a scatter plot by using SAS software. It also describes how to overlay multiple prediction ellipses for subpopulations. What is a prediction ellipse? A […]

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I am not an econometrician

July 21, 2014
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I am not an econometrician

I am a statistician, but I have worked in a department of predominantly econometricians for the past 17 years. It is a little like an Australian visiting the United States. Initially, it seems that we talk the same language, do the same sorts of things, and have a very similar culture. But the longer you stay there, the more you realise there are differences that run deep and affect the…

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