Como crear informes R-Markdow con R-Studio.

(This article was first published on R-exercises, and kindly contributed to R-bloggers) Introduction R Markdown is one of the most popular data science tools and is used to save and execute code to create exceptional reports whice are easily shareable. The documents that R Markdown provides are fully reproducible and support a wide variety of…

via How to create reports with R Markdown in RStudio — R-bloggers

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Descargar S&P 500 Stock Data desde Google/Quandl con R.

(This article was first published on R – Curtis Miller’s Personal Website, and kindly contributed to R-bloggers) DISCLAIMER: Any losses incurred based on the content of this post are the responsibility of the trader, not me. I, the author, neither take responsibility for the conduct of others nor offer any guarantees. None of this should…

via Downloading S

Disponible R 3.4.1

(This article was first published on R – R-statistics blog, and kindly contributed to R-bloggers) R 3.4.1 (codename “Single Candle”) was released several days ago. You can get the latest binaries version from here. (or the .tar.gz source code from here). As mentioned last week by David Smith, R 3.4.1 includes several Windows related bug fixed: including an issue sometimes…

via R 3.4.1 is released – with some Windows related bug-fixes — R-bloggers

Descomposición temporal con R

 

Resumen:

Evaluación de diferentes funciones descomposición temporal de R. Se utiliza como ejemplo la serie mensual de las concentraciones atmosféricas de CO2 en partes por millón (ppm) en Mauna Loa (Hawai),desde 1959 a 1979 .

Las funciones de R analizadas son: decompose, stl, decomp y descomponer. En los análisis gráficos muestran una gran simulitud, tanto en lo relativo a la serie de tendencia T(t), como a la estacionalidad S(t). La serie irregular I(t) acepta la hipótesis de normalidad en los test estadísticos KS y CVM en todos los casos, pero con autocorrelación serial.

 

descomposición temporal con R

 

En R-Pub:

Descomposición temporal con R

Ordinary Least Squares (OLS) linear regression in R.

(This article was first published on Environmental Science and Data Analytics, and kindly contributed to R-bloggers) Ordinary Least Squares (OLS) linear regression is a statistical technique used for the analysis and modelling of linear relationships between a response variable and one or more predictor variables. If the relationship between two variables appears to be linear,…

via Ordinary Least Squares (OLS) Linear Regression in R — R-bloggers

Stock Trading Analytics and Optimization in Python with PyFolio, R’s PerformanceAnalytics, and backtrader.

(This article was first published on R – Curtis Miller’s Personal Website, and kindly contributed to R-bloggers) Introduction Having figured out how to perform walk-forward analysis in Python with backtrader, I want to have a look at evaluating a strategy’s performance. So far, I have cared about only one metric: the final value of the…

via Stock Trading Analytics and Optimization in Python with PyFolio, R’s PerformanceAnalytics, and backtrader — R-bloggers