2297 search results for "Time series"

Part 4a: Modelling – predicting the amount of rain

April 6, 2015
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Part 4a: Modelling – predicting the amount of rain

In the fourth and last part of this series, we will build several predictive models and evaluate their accuracies. In Part 4a, our dependent value will be continuous, and we will be predicting the daily amount of rain. Then, in Part 4b, we will deal with the case of a binary outcome, which means we will assign probabilities to...

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The Logical Invest “Hell On Fire” Replication Attempt

April 6, 2015
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The Logical Invest “Hell On Fire” Replication Attempt

This post is about my replication attempt of Logical Invest’s “Hell On Fire” strategy — which is its Universal Investment … Continue reading →

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ANOVAs and Geomorph

April 1, 2015
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Within geomorph are several functions that perform analysis of variance (ANOVA), includingprocD.lm()procD.pgls()advanced.procD.lm()pairwiseD.test()pairwise.slope.test()trajectory,analysis()bilat.symmetry()plotAllometry() Inherent in all of these functions is a common philosophy for ANOVA (although other philosophies exist).  The geomorph ANOVA philosophy is that: (1) resampling (randomization) procedures are used to generate empirical sampling distributions to assess significance of effects, (2) effect sizes are estimated as standard deviates from such...

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Seeing the Forest and the Trees – a parallel machine learning example

April 1, 2015
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Seeing the Forest and the Trees – a parallel machine learning example

Parallelizing Random Forests in R with BatchJobs and OpenLava By: Gord Sissons and Feng Li In his series of blogs about machine learning, Trevor Stephens focuses on a survival model from the Titanic disaster and provides a tutorial explaining how decision trees tend to over-fit models yielding anomalous predictions. How do we build a better

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Fundamentals of R: Free course by General Assembly & DataCamp

March 31, 2015
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Fundamentals of R: Free course by General Assembly & DataCamp

Together with General Assembly, DataCamp created a free set of videos on the fundamentals of R. Discover it now! In a series of short videos, the team behind DataCamp teaches you about the fundamentals of R, an open-source statistical programming language. Use this course to understand the advantages and disadvantages of R, and discover at the same The post

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Parallel R with BatchJobs

March 28, 2015
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Parallel R with BatchJobs

Parallelizing R with BatchJobs – An example using k-means Gord Sissons, Feng Li Many simulations in R are long running. Analysis of statistical algorithms can generate workloads that run for hours if not days tying up a single computer. Given the amount of time R programmers can spend waiting for results, getting acquainted parallelism makes

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R style default plot for Pandas DataFrame

March 28, 2015
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R style default plot for Pandas DataFrame

The default plot method for dataframes in R is to show each numeric variable in a pair-wise scatter plot. I find this to be a really useful first look at dataset, both to see correlations and joint distributions between variables, but also to quickly diagnose potential strangeness like bands of repeating values or outliers. From

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rClr 0.7-4 released

March 26, 2015
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rClr 0.7-4 released

Version 0.7-4 of rClr (source code mirrored on GitHub), a package to access arbitrary .NET code seamlessly and in-process, has been released.This is a maintenance release with an important fix to memory management. In some circumstances, passing data ...

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NASDAQ 100 Couples

March 25, 2015
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NASDAQ 100 Couples

Heaven, I’m in heaven, and my heart beats so that I can hardly speak, and I seem to find the happiness I seek, when we’re out together dancing cheek to cheek (Cheek To Cheek, Irving Berlin) There are about 6.500 available packages in CRAN repository. If I were a superhuman, able to learn one package … Continue reading...

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Factor Evaluation in Quantitative Portfolio Management

March 23, 2015
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Factor Evaluation in Quantitative Portfolio Management

When it comes to managing a portfolio of stocks versus a benchmark the problem is very different from defining an absolute return strategy. In the former one has to hold more stocks than in the later where no stocks at all can be held  if there is not good enough opportunity.  The reason for that is the tracking error. This

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