The package ‘Seasonal’ facilitates seasonal adjustment in R. The R package provides an easy-to-handle wrapper around the X-13ARIMA-SEATS Fortran libraries provided by the US Census Bureau. X-13ARIMA-SEATS is the state-of-the-art seasonal adjustment software produced, distributed, and maintained by the Census Bureau. Continue reading Seasonal Adjustment in R
Learning a new programming language is costly. Usually it takes a considerable amount of time to get acquainted with a new language. Especially the first phase can be painful and frustrating. The good thing is that with enough time and effort most of us will learn how to master a programming language eventually. However, note that, once we are comfortable with one language, we hardly want to change again. It turns out that the cost of abandoning on programming language and switch to another are even higher than at the beginning. Knowing this, we really want to make sure not to invest in the wrong language. There might be nothing worse than after finally mastering a programming language, recognizing that there is no use for this language anymore. While in a former post I highlighted reason why to use R, I concentrate on the Pros and Cons of R in this post.
Advantages of R
Why should you use R?
There exists several reasons why one should start using R. During the last decade R has become the leading tool for statistics, data analysis, and machine learning. By now, R represents a viable alternative to traditional statistical programs such as Stata, SPSS, SAS, and Matlab. The reasons for R’s success are manifold. Continue reading Why R?
In this post I am going to explain how to enable GUI root access on Debian 9. Instructions for Debian 10 are similar and can be found here. At this point I should warn you that using the root account is dangerous as you can ruin your whole system. Try to follow this guide exactly.
What is seasonal adjustment?
Seasonal adjustment refers to a statistical technique that tries to quantify and remove the influences of predictable seasonal patterns to reveal nonseasonal changes in data that would otherwise be overshadowed by the seasonal differences. Seasonal adjustments provide a Continue reading Seasonal adjustment