Posts

Weighted LOESS (LOcal regrESSion)

LOcal regrESSion (LOESS) or LOcally WEighted Scatter-plot Smoother (LOWESS) LOESS or LOWESS is a nonparametric technique to fit a smooth curve through points in a scatter plot. This approach uses locally estimated linear regression at its core. The following code illustrates how to include a loess line using the ggplot2 package. library(ggplot2) set.seed(1) x <- rnorm(60) y <- c(rnorm(40), 10, rnorm(19)) df <- data.frame(x=x, y=y) ## Without weights ggplot(data=df, aes(x=x, y=y)) + geom_point() + geom_smooth(method=loess, legend=FALSE) Furthermore your can plot loess smoothing weighting the observations as follows:

Reporting your model outputs

Let’s see how to format your model outputs with parameters package in R by Lüdecke et al. (2020). Fit a simple linear regression model #install.packages("parameters") library(parameters) library(magrittr) library(gt) library(see) model <- lm(Volume ~ Height + Girth, data=trees) Reporting model parameter estimates model %>% model_parameters() Parameter | Coefficient | SE | 95% CI | t(28) | p -------------------------------------------------------------------- (Intercept) | -57.99 | 8.64 | [-75.68, -40.29] | -6.71 | < .

Organize your priorities using CalendR package in R

Maintaining a calendar to organize your events allows for having more smooth and productive day. In this post, I will show you some basic functionalities in CalendaR package.

Ratio matters: change the way you see things!

Aspect ratio: what it is and why it is. How often do you fix aspect ratio?

Highlight data points in a scatterplot

Highlight selected points in the scatterplot

Import data into R: Overwritten object names

Read data files

Working with built-in data sets in R

How to view datasets in a particular package, or or list the available data sets?

Small things matter!

Checks whether your package name is taken or available !! install.packages("available") library(available) available("seer") ── seer ─────────────────────────────────────────── Name valid: ✔ Available on CRAN: ✖ Available on Bioconductor: ✖ Available on GitHub: ✖ Abbreviations: http://www.abbreviations.com/seer Wikipedia: https://en.wikipedia.org/wiki/seer Wiktionary: https://en.wiktionary.org/wiki/seer Urban Dictionary: short for "serious", common [lingo] between [douche bags] and fags. other common words are used such as "[yon]" and "non" http://seer.urbanup.com/5727698 Sentiment:??? This means the name seer is taken in both CRAN and GitHub.

Parameter, Statistic, Random Variable, Estimator and Estimate

The most common problem while learning Statistics is that students’ lack of understanding of the basic terminologies, notations, definitions and concepts. Think of Statistics as building blocks, and you need a solid foundation to move forward. Here, I explain five common terms in Statistics: i) Parameter, ii) Statistic, iii) Random Variable, iv) Estimator, v) Estimate and their notations. I will start with the definition of Population and Sample. A population is a complete collection of individuals/ objects that we are interested in.

Happy Women in Maths Day - 12 May 2020

Nature is my biggest inspiration for my love and passion for mathematics.