The fifth conference on R in Insurance will be held on 8 June 2017 at ENSAE. ENSAE is the Paris Graduate School for Economics, Statistics and Finance.The intended audience of the conference includes both academics and practitioners who are active or interested in the applications of R in Insurance.This one-day ... [Read more...]

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I just wrote a new chapter for my students describing how to subset a data frame in R. The full text is available at https://docs.google.com/document/d/1K5U11-IKRkxNmitu_lS71Z6uLTQW_fp6QNbOMMwA5J8/edit?usp=sharing but here’s a preview: Let’s load ... [Read more...]

Here is a short post which ranks IPL batsmen and bowlers post the 2016 IPL season. These are based on match data from Cricsheet. I had already ranked IPL players in my post yorkr ranks IPL batsmen and bowlers, but that was mid IPL 2016 season. This post will be final ranking ... [Read more...]

Survival analysis corresponds to a set of statistical methods for investigating the time it takes for an event of interest to occur. In this chapter, we start by describing how to fit survival curves and how to perform logrank tests comparing the survival time of two or more groups of ... [Read more...]

Version 1.4.10 of RSiteCatalyst brings a handful of new Get* methods, QueueDatawarehouse and a couple of bugs fixes/low-level code improvements. QueueDatawarehouse The most useful user-facing change IMO is the addition of the QueueDatawarehouse metho... [Read more...]

I’m very pleased to announce survminer 0.2.4. It comes with many new features and minor changes. Install survminer with:

install.packages("survminer")

To load the package, type this:

library(survminer)

ContentsNew features Minor changes Bug fixes Summary of survival curves Plot survival curves Determine the optimal cutpoint for continuous variables Facet the output ... [Read more...]

In this section, you’ll find R packages developed by STHDA for easy data analyses. factoextra factoextra let you extract and create ggplot2-based elegant visualizations of multivariate data analyse results, including PCA, CA, MCA, MFA, HMFA and clustering methods. Overview ____factoextra Site Link ____ survminer survminer provides functions for facilitating ... [Read more...]

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Previously, we described the basic methods for analyzing survival data, as well as, the Cox proportional hazards methods to deal with the situation where several factors impact on the survival process. In the current article, we continue the series by describing methods to evaluate the validity of the Cox model ... [Read more...]

The Cox proportional-hazards model (Cox, 1972) is essentially a regression model commonly used statistical in medical research for investigating the association between the survival time of patients and one or more predictor variables. In the previous chapter (survival analysis basics), we described the basic concepts of survival analyses and methods for ... [Read more...]

Len Kiefer, Deputy Chief Economist at Freddie Mac, recently posted an analysis of global housing price trends based on the international house price database (from the Dallas Fed). Using those data, Kiefer compared housing trends price increases (and in a couple of places like Spain and Ireland, decreases) across 24 countries. ... [Read more...]

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Survival analysis corresponds to a set of statistical approaches used to investigate the time it takes for an event of interest to occur. Survival analysis is used in a variety of field such as: Cancer studies for patients survival time analyses, Sociology for “event-history analysis”, and in engineering for “failure-time ... [Read more...]

INTRODUCTION TO SHINY Shiny is a package from RStudio that can be used to build interactive web pages with RStudio which is is an open source set of integrated tools designed to help you be more productive with R and you can download it from here. Use the examples in ... [Read more...]

In R, when a function returns an error, there is an easy way to figure out which command have triggered the error. [Read more...]

[This article was first published on databait, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. Previous blog post on the Kelly CriterionAs pointed out in a previous blog post, the Kelly Criterion is an interesting option to decide on position sizing in portfolio selection. While the previous post looked at single stocks, I will today show how to optimize position sizes for a portfolio with multiple stocks. The core functionAt the core of my portfolio optimization is this function: 12345678910111213opt_portfolio <-function(shares, dpf, maxshare) { # calculate portfolios return vector exp_returns <- dpf%*%shares obj = -sum(log(1+exp_returns)) weight.penalty = 1000*(1-sum(shares))^2 # max share penalty: maxpen <- sum(shares[shares>maxshare])*1000 return(obj + weight.penalty + maxpen)} The function has three parameters. shares is the vector of shares (position size for each stock) that is going to be estimated by optimization. dpf is a matrix where each stock is a column and each line contains the daily stock price movements like e.g.: diff(stock)/lag(stock). The maxshare option can be used to restrict the position size of a single stock to a [...] [Read more...]

A new version 0.1.0 of RcppCCTZ arrived on CRAN this morning. It brings a number of new or updated things, starting with new upstream code from CCTZ as well as a few new utility functions. CCTZ is a C++ library for translating between absolute and civil times using the rules of ... [Read more...]