Tag: regression

Feed: SAS Blogs. Author: Rick Wicklin. I recently wrote about a simple statistical formula that approximates the wind chill temperature, which is the cumulative effect of air temperature and wind on the human body. The formula uses two independent variables (air temperature and wind speed) to predict the wind chill temperature. This article describes how to use SAS to create line charts and heat maps that visualize the formula. For the heat map, I show how to overlay numerical values and to choose colors for the numbers so that the text is more readable. An ... Read More

Feed: R-bloggers. Author: R | Joshua Entrop. [This article was first published on R | Joshua Entrop, 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. In this blog post we will optimise a Cox proportional hazard model using a maximum likelihood estimation (MLE) method. For this we are first going to define the likelihood function of our Cox model and its partial first derivatives, sometimes called the score function. Later we will pass ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: ajit jaokar. This blog is the second part in a series. The first part is The Bayesian vs frequentist approaches: implications for machine le... In part one, we summarized that: There are three key points to remember when discussing the frequentist v.s. the Bayesian philosophies. The first, which we already mentioned, Bayesians assign probability to a specific outcome. Secondly, Bayesian inference yields probability distributions while frequentist inference focusses on point estimates. Finally, in Bayesian statistics, parameters are assigned a probability whereas in the frequentist approach, the parameters are fixed. Thus, in ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: akash. Increased consumption of data, more powerful computing, and the strong inclination towards data-driven decisions in business have made data science a crucial part of today's business environment. According to IBM, there is a huge demand for data scientists and data analysts in the present time. Python and R are the two most popular tools for programming for data science. Python and R both are open-source and free and were developed back in the early 1990s. For practitioners of machine learning and data science, these two tools are absolutely essential. While ... Read More

Feed: R-bloggers. Author: R on OSM. [This article was first published on R on OSM, 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. We start a new series on neural networks and deep learning. Neural networks and their use in finance are not new. But are still only a fraction of the research output. A recent Google scholar search found only 6% of the articles on stock price price forecasting discussed neural networks ... Read More

Feed: R-bloggers. Author: Higher Order Functions. [This article was first published on Higher Order Functions, 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. For a long time, I’ve been curious about something. It is a truth I’ve seen casually dropped in textbooks, package documentation, and tweets: random effects and penalized smoothing splines are the same thing. It sounds so profound and enlightened. What does it mean? How are they the same? What deep ... Read More

Feed: R-bloggers. Author: R Views. [This article was first published on R Views, 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. Two hundred thirty new packages made it to CRAN in January. Here are my “Top 40” selections in ten categories: Data, Finance, Genomics, Machine Learning, Medicine, Science, Statistics, Time Series, Utilities, and Visualization. Data igoR v0.1.1: Provides tools to extract information from the Intergovernmental Organizations (‘IGO’) Database , version 3, provided by ... Read More

Feed: What's New. Author: Ana Crisan. Editor's note: This article originally appeared in the Tableau Engineering Blog. Data science has exploded over the past decade, changing the way that we conduct business and prepare the next generation of young people for the jobs of the future. But this rapid growth was coupled with a still evolving understanding of data science work, which has led to a lot of ambiguity toward how we can use data science to derive actionable insights from our piles of data. Having had my own career shaped by the growth of data science, I wanted to dig ... Read More

Feed: SAS Blogs. Author: Rick Wicklin. In cold and blustery conditions, the weather forecast often includes two temperatures: the actual air temperature and the wind chill temperature. The wind chill temperature conveys the cumulative effect of air temperature and wind on the human body. The goal of the wind-chill scale is to communicate the effect of the wind by giving an equivalent hypothetical scenario in which the temperature is colder but there is no wind. For example, if the wind chill temperature is 0 degrees, it means that the outdoor air temperature and wind combine to ... Read More

Feed: R-bloggers. Author: Economics and R - R posts. Chapter 5 of my course Empirical Economics with R covers instrumental variable (IV) estimation. While being one of the most popular methods in academic economic papers for estimating causal effects (see e.g. the statistics here), I was not sure whether to introduce IV estimation in this Bachelor level course. My hesitation was due to the fact that despite peer reviews instrument exogeneity seems debatable in some studies and I feared worse if today’s students would indeed start using IV as practitioners in their jobs. But then this quote from the textbook ... Read More