3275 search results for "Map"

Include uncertainty in a financial model

April 1, 2014
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Include uncertainty in a financial model

Here’s a post that appears on my new website, ragscripts.com. On-line resources for analysts are often either too general to be of practical use or too specialised to be accessible. The aim of ragscripts.com is to remedy this by providing start to finish directions for complex analytical tasks. The site is under construction at the … Continue reading...

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Calendar charts with googleVis

April 1, 2014
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Calendar charts with googleVis

My little series of posts about the new googleVis charts continues with calendar charts. Google's calendar charts are still in beta, but they provide already a nice heat map visualisation of calendar year data. The current development version of google...

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Using iterators for sparse vectors and matrices

March 31, 2014
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Using iterators for sparse vectors and matrices

Iterating over a sparse vector Consider the following vector: idx1 <- c(2L, 0L, 4L, 0L, 7L) A sparse representation of this vector will tell that at entries 1,3,5 (or at entries 0,2,4 if we are 0-based) we will find the values 2,4,7. Using Eigen via RcppEigen we can obtain the coercion with .sparseView(). We can iterate over all elements (including the zeros) in a sparse vector...

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Using iterators for sparse vectors and matrices

March 31, 2014
By
Using iterators for sparse vectors and matrices

Iterating over a sparse vector Consider the following vector: idx1 <- c(2L, 0L, 4L, 0L, 7L)A sparse representation of this vector will tell that at entries 1,3,5 (or at entries 0,2,4 if we are 0-based) we will find the values 2,4,7. Using Eigen via RcppEigen we can obtain the coercion with .sparseView(). We can iterate over all elements (including the zeros) in a sparse vector...

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Bayesian Data Analysis [BDA3 – part #2]

March 30, 2014
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Bayesian Data Analysis [BDA3 – part #2]

Here is the second part of my review of Gelman et al.’ Bayesian Data Analysis (third edition): “When an iterative simulation algorithm is “tuned” (…) the iterations will not in general converge to the target distribution.” (p.297) Part III covers advanced computation, obviously including MCMC but also model approximations like variational Bayes and expectation propagation

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Introduction to PortfolioAnalytics

March 29, 2014
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Introduction to PortfolioAnalytics

PortfolioAnalytics Basics This is a guest post by Ross Bennett. Ross is currently enrolled in the University of Washington Master of Science in Computational Finance & Risk Management program with an expected graduation date of December 2014. He worked on the PortfolioAnalytics...

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A Simple Introduction to the Graphing Philosophy of ggplot2

March 28, 2014
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A Simple Introduction to the Graphing Philosophy of ggplot2

Blog post: a very basic introduction to building data plots using ggplot2 in R. #Rstats

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Why use R? Five reasons.

March 27, 2014
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Why use R? Five reasons.

In this post I will go through 5 reasons: zero cost, crazy popularity, awesome power, dazzling flexibility, and mind-blowing support. I believe R is the best statistical programming language to learn. As a blogger who has contributed over 150 posts in Stata and over 100 in R I have extensive experience with both a proprietary statistical programming language...

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Assign n Email Addresses to x Cells, Intrinsically (Part II)

March 27, 2014
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Part I showed the concept and general technique of a method of assigning n email addresses to x cells pseudo-randomly, without the need for maintaining a log of each assignment.The earlier post considered the basic case of each cell being assigned approximately the same quantity of email addresses. In practice, cell sizes often vary. Below is a technique that...

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GIS in R: Part 1

March 27, 2014
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GIS in R: Part 1

I messed around with R for years without really learning how to use it properly. I think it’s because I could always throw my hands up when the going got tough and run back and cling the skirts of Excel or JMP or Systat. I finally learned how to use R when I needed to

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