# 1233 search results for "regression"

## “Statistical Models with R” Course – Milano, October 24-25, 2013

September 19, 2013
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MilanoR, in collaboration with Quantide, organizes "Statistical Models with R" Course October 24-25, 2013 Course description This two-day course shows a wide variety of statistical models with R ranging from Linear Models (LM) to Generalized Linear Models (GLM) modelling, in … Continue reading →

## informative hypotheses (book review)

September 18, 2013
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The title of this book Informative Hypotheses somehow put me off from the start: the author, Hebert Hoijtink, seems to distinguish between informative and uninformative (deformative? disinformative?) hypotheses. Namely, something like H0: μ1=μ2=μ3=μ4 is “very informative” and the alternative Ha is completely uninformative, while the “alternative null” H1: μ1<μ2=μ3<μ4 is informative. (Hence the < signs on

## PirateGrunt goes to the CLRS

September 16, 2013
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Yesterday, I had the great pleasure to speak about using R for loss reserving at the Casualty Loss Reserving Seminar in Boston. My time was spent talking about MRMR, an R package that I’ve created. Version 0.1.2 is now on CRAN, but as there are a couple of bugs, I’d suggest waiting until version 0.1.3

## Forecasting with daily data

September 16, 2013
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I’ve had several emails recently asking how to forecast daily data in R. Unless the time series is very long, the simplest approach is to simply set the frequency attribute to 7. y <- ts(x, frequency=7) Then any of the usual time series forecasting methods should produce reasonable forecasts. For example library(forecast) fit <- ets(y) fc <- forecast(fit) plot(fc)...

## New robust statistical functions in WRS package – Guest post by Rand Wilcox

September 16, 2013
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Today a new version (0.23.1) of the WRS package (Wilcox’ Robust Statistics) has been released. This package is the companion to his rather exhaustive book on robust statistics, “Introduction to Robust Estimation and Hypothesis Testing” (Amazon Link de/us). For a fail-safe installation of the package, follow this instruction. As a guest post, Rand Wilcox describes

## BCEA in UseR!

September 13, 2013
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In a recent post, I had hinted at big news for BCEA $-$ I thought it was pretty much a done deal, but because it wasn't yet set in stone, I didn't want to jinx it...But now I've sorted all the details with Springer, who have asked me to write a book on the...

## Alpha Testing RevoScaleR running in Hadoop

September 13, 2013
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by Joseph Rickert At Revolution Analytics our mission is to establish R as the driver for Enterprise level computational frameworks. In part, this means that a data scientist ought to be able to develop an R based application in one context, e.g. her local PC, and then get it moving by changing horses on the fly (so to speak)...

## Non-observable vs. observable heterogeneity factor

September 11, 2013
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This morning, in the ACT2040 class (on non-life insurance), we’ve discussed the difference between observable and non-observable heterogeneity in ratemaking (from an economic perspective). To illustrate that point (we will spend more time, later on, discussing observable and non-observable risk factors), we looked at the following simple example. Let  denote the height of a person. Consider the following dataset >...

## Online course on forecasting using R

September 10, 2013
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I am teaming up with Revolution Analytics to teach an online course on forecasting with R. Topics to be covered include seasonality and trends, exponential smoothing, ARIMA modelling, dynamic regression and state space models, as well as forecast accuracy methods and forecast evaluation techniques such as cross-validation. I will talk about some of my consulting experiences, and explain the...