680 search results for "robust"

anytime 0.1.1: More robust

November 27, 2016
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CRAN just accepted the newest release 0.1.1 of anytime, following the previous five releases since September. anytime is a very focussed package aiming to do just one thing really well: to convert anything in integer, numeric, character, factor, ordered, ... format to POSIXct (or Date) objects -- and to do so without requiring a format string. See the...

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Your data vis “Spidey-sense” & the need for a robust “utility belt”

June 16, 2016
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Your data vis “Spidey-sense” & the need for a robust “utility belt”

@theboysmithy did a great piece on coming up with an alternate view for a timeline for an FT piece. Here’s an excerpt (read the whole piece, though, it’s worth it): Here is an example from a story recently featured in the FT: emerging- market populations are expected to age more rapidly than those in developed... Continue reading →

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Visual contrast of two robust regression methods

Visual contrast of two robust regression methods

Robust regression For training purposes, I was looking for a way to illustrate some of the different properties of two different robust estimation methods for linear regression models. The two methods I’m looking at are: least trimmed squares, implemented as the default option in lqs() a Huber M-estimator, implemented as the default option in rlm() Both functions...

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An Update to the Robustness Heuristic and a Variation of a Volatility Strategy

December 10, 2014
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An Update to the Robustness Heuristic and a Variation of a Volatility Strategy

So, before revealing a slight wrinkle on the last strategy I wrote about, I’d like to clear up a bit … Continue reading →

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A New Volatility Strategy, And A Heuristic For Analyzing Robustness

December 4, 2014
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A New Volatility Strategy, And A Heuristic For Analyzing Robustness

This post is motivated by a discussion that arose when I tested a strategy by Frank of Trading The Odds … Continue reading →

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Intermission: A Quick Thought on Robust Kurtosis

September 10, 2014
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Intermission: A Quick Thought on Robust Kurtosis

This post was inspired by some musings from John Bollinger that as data in the financial world wasn’t normally distributed, … Continue reading →

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The Continuing Search For Robust Momentum Indicators: the Fractal Adaptive Moving Average

June 22, 2014
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The Continuing Search For Robust Momentum Indicators: the Fractal Adaptive Moving Average

Following from the last post and setting aside the not-working-as-advertised Trend Vigor indicator, we will turn our attention to the … Continue reading →

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Reanalyzing the Schnall/Johnson “cleanliness” data sets: New insights from Bayesian and robust approaches

June 2, 2014
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Reanalyzing the Schnall/Johnson “cleanliness” data sets: New insights from Bayesian and robust approaches

I want to present a re-analysis of the raw data from two studies that investigated whether physical cleanliness reduces the severity of moral judgments – from the original study (n = 40; Schnall, Benton, & Harvey, 2008), and from a direct replication (n = 208, Johnson, Cheung, & Donnellan, 2014). Both data sets are provided

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A principle of writing robust R program

February 14, 2014
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Writing R code can be very easy. It depends on how much you want to achieve with your code and what features you want your code to support. To test a random thought that needs some statistical evidence, you only need to casually import data, slightly transform the data to a necessary form, and perform some statistical tests and see...

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

September 16, 2013
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New robust statistical functions in WRS package – Guest post by Rand Wilcox

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

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