Implement and benchmark a fast Kendall's tau-a in C++ via Rcpp against base R, discuss tie handling (tau-b), and when to move from R to C++.
what each tool solves, when to reach for it, and ready-to-paste code.
This post explores the performance of various compression techniques in R for reading and writing operations, highlighting file size, speed, and memory usage.
This post explores the performance of various data formats in R for reading and writing operations, highlighting file size, speed, and memory usage.
1 Polynomial models 2 Fractional polynomial models 2.1 Finding optimal power Values in fractional polynomials 3 Spline models 3.1 Example 3.2 Challenges 3.3 Selection process for spline models 4 Citation The ability to accurately model and interpret complex data sets is paramount. This technical exploration delves into three sophisticated modelling techniques: - Polynomial Models, - Fractional Polynomials, and - Spline Models. Each of these models serves as a fundamental tool in the statistical toolkit, enabling us to capture and understand the intricacies of linear and non-linear relationships inherent in real-world data.
General idea The Concordance Correlation Coefficient (CCC) is a statistical measure designed to evaluate the agreement between two sets of measurements, such as those represented by two random variables, XXX and YYY. Mathematically, the CCC is defined as: ρc=2σx,yσx2+σy2+(μx−μy)2=2ρσxσyσx2+σy2+(μx−μy)2=ρ×Cb.\rho_c = \frac{2\sigma_{x,y}}{\sigma_x^2 + \sigma_y^2 + (\mu_x - \mu_y)^2} = \frac{2\rho\sigma_x\sigma_y}{\sigma_x^2 + \sigma_y^2 + (\mu_x - \mu_y)^2} = \rho \times C_b.ρc=σx2+σy2+(μx−μy)22σx,y=σx2+σy2+(μx−μy)22ρσxσy=ρ×Cb. In this formula, σx\sigma_xσx and σy\sigma_yσy are the standard deviations of XXX and YYY, respectively, showing the variability within each set of measurements.
Introduction In R programming, efficiency is key. Snippets, small reusable blocks of code, are a cornerstone in achieving this. This post delves into the world of snippets, offering both novice and seasoned R programmers insights into their power and versatility. What are snippets? In R programming, snippets are more than just pre-written bits of code; they are dynamic templates designed to streamline code writing and editing. Snippets in R can contain placeholders, which are special fields that can be easily tabbed through and filled in by the programmer.
The golem package In the world of R programming, Shiny applications let us make interactive web apps using R code. The golem package (Fay et al. 2021) makes it easier to develop these apps. It brings new tools and methods to this area, helping developers handle complex tasks more simply. Making Things with Structure Think of making a sculpture out of clay. At first, the big lump of clay can be hard to handle.
tl;dr Many different variables affect how the pandemic progresses and it is extremely difficult to identify each one, and precisely measure them. The data we have is surely innacurate, but could be a good proxy for understanding the behaviour of the coronavirus outbreak We developed a statistical model to obtain short-term forecasts of the number of COVID-19 cases We constantly update forecasts and make all results freely available to any country in the world through a web app How many people will get infected tomorrow?
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