The tsbox package makes life with time series in R easier. It is built around a set of functions that convert time series of different classes to each other. They are frequency-agnostic, and allow the user to combine time series of multiple non-standard and irregular frequencies. A detailed overview of ...

The tsbox package makes life with time series in R easier. It is built around a set of functions that convert time series of different classes to each other. They are frequency-agnostic, and allow the user to combine time series of multiple non-standard and irregular frequencies. A detailed overview of ...

Continuing on the below post, I am going to use a support vector machine (SVM) to predict combined miles per gallon for all 2019 motor vehicles. Part 1: Using Decision Trees and Random Forest to Predict MPG for 2019 Vehicles Part 2: Using Gradient Boosted Machine to Predict MPG for 2019 Vehicles The raw data ...

Continuing on the below post, I am going to use a support vector machine (SVM) to predict combined miles per gallon for all 2019 motor vehicles. Part 1: Using Decision Trees and Random Forest to Predict MPG for 2019 Vehicles Part 2: Using Gradient Boosted Machine to Predict MPG for 2019 Vehicles The raw data ...

I am excited to announce vtreat is now available for Python on PyPi, in addition for R on CRAN. vtreat is: A data.frame processor/conditioner that prepares real-world data for predictive modeling in a statistically sound manner. vtreat prepares variables so that data has fewer exceptional cases, making it ...

A NICE ONELINER HERE? This post is an explainer about the small sample experiment and determining the ideal sample size for inference. Economic perspectives and business logic Brewing beer at scale One of the problems William S. Gosset worked on was determining the quality of Malt. To brew beer you ...

Introduction Recently, I stepped into the AWS ecosystem to learn and explore its capabilities. I’m documenting my experiences in these series of posts. Hopefully, they will serve as a reference point to me in future or for anyone else following this...

Fred Viole shared a great “data only” R solution to the forecasting tides problem. The methodology comes from a finance perspective, and has some great associated notes and articles. This gives me a chance to comment on the odd relation between prediction and profit in finance. If there really was ...

Introduction In the previous post, we focused on setting up declarative Jenkins pipelines with emphasis on parametrizing builds and using environment variables across pipeline stages. In this post, we look at various tips that can be useful when automating R application testing and continuous integration, with regards to orchestrating parallelization, ...

Genesis I started to use continuous integration with gitlab a few weeks ago and up to a few days was really happy with rocker image (basically docker + R). I became ambitious and started to write a markdown that was comparing R and Python speed on...

As engineers, it is not uncommon to be asked to determine whether or not two different configurations of a product perform the same. Perhaps we are asked to compare the durability of a next-generation prototype to the current generation. Sometimes we are testing the flexibility of our device versus a ...

Let \(\rho_{XY}\) be the correlation between the stochastic variables \(X\) and \(Y\) and similarly for \(\rho_{XZ}\) and \(\rho_{YZ}\). If we know two of these, can we say anything about the third? In a recent blog post I dealt with the problem mathematically and I used the concept ...

tl;dr: P-values are tail probabilities calculated from the sampling distribution of a sample-based statistic. This sampling distribution will depend on the size of the sample, the statistic being calculated and assumptions about the random population from which the data could have been sampled. For a few cases, analytical p-values ...

Mastered the basics of data cleaning in R? Take your data cleansing skills to the next level with this advanced data cleaning course for R coders. The post New Course: Learn Advanced Data Cleaning in R appeared first on Dataquest.

I was recently fortunate to be invited to speak with an impressive group of high-school students as a part of the Germination Project. They came to Penn to learn about innovation in health care and I spoke with them about how we’re using Data Science to improve patient outcomes.