Science Research Weekly

In this episode, I stretch before vigorous calisthenics, give a thumbs up to O’Reilly coding books, get to the bottom of R vectorization, try not to panic during   debugging, and showcase the R-package ‘fauxnaif’.

References:

R   packages:

In this episode, I jump into Julia packages, estimate how to pronounce the generalized Kibria-Lukman estimator, commiserate with Python, and showcase the R-package ‘rsconnect’.

References:

R-packages:

In this episode, I play with jackknives, chuckle over Python, list upcoming R conferences, and showcase the R-package ‘RcppBDT’.

References:

Additive Noise-Induced System Evolution (ANISE)

Face Recognition in Single Sample Per Person Fusing Multi-Scale Features Extraction and Virtual Sample Generation Methods

An Epidemiological Compartmental Model With Automated Parameter Estimation and Forecasting of the Spread of COVID-19 With Analysis of Data From Germany and Brazil

Accelerating Jackknife Resampling for the Canonical Polyadic Decomposition

The last Python 3.11 alpha (3.11.0a7) is available

New methods for solving differential equations in SAS

Pascal matrices and inverses

Enhancements to HTML Documentation

Some discussion of “how to get confident with statistics”: Reading, practicing, and questioning

Permutation vs Combination: Differences & Examples

Chi-Square Goodness of Fit Test: Uses & Examples

SPSS Syntax 101

The sftime Package

To impute or not: the case of an RCT with baseline and follow-up measurements

Why you should(n’t) care about Monads if you’re an R programmer

Bayesian Estimation by using rjags Package

Upcoming R conferences (2022)

R-packages:

clusterHD: Tools for Clustering High-Dimensional Data

Allspice: RNA-Seq Profile Classifier

cheatR: Catch Cheaters

spooky: Time Feature Extrapolation Using Spectral Analysis and Jack-Knife Resampling

taxonbridge: Create Custom Taxonomies Based on the NCBI Taxonomy and GBIF Backbone Taxonomy

wrMisc: Analyze Experimental High-Throughput (Omics) Data

findInFiles: Find Pattern in Files

mclogit: Multinomial Logit Models, with or without Random Effects or Overdispersion

aRtsy: Generative Art with 'ggplot2'

glmm: Generalized Linear Mixed Models via Monte Carlo Likelihood Approximation

glmtoolbox: Set of Tools to Data Analysis using Genera

RcppBDT: 'Rcpp' Bindings for the Boost Date_Time Library

In this episode, I drink from the firehose of CRAN packages, learn a use for ‘two truths and a lie’ in the statistics classroom, and showcase the R-package ‘pipeliner’.

References:

https://www.frontiersin.org/articles/10.3389/fams.2022.848898/abstract

https://www.frontiersin.org/articles/10.3389/fams.2022.852314/full

https://stat.ethz.ch/pipermail/r-announce/2022/000681.html

https://cran.r-project.org/web/packages/available_packages_by_date.html

https://www.spss-tutorials.com/open-excel-file-in-spss/

https://www.spss-tutorials.com/spss-missing-values-for-string-variables/

https://errorstatistics.com/2022/04/05/insevere-tests-of-severe-testing/

https://statmodeling.stat.columbia.edu/2022/04/04/two-truths-and-a-lie-as-a-class-participation-activity/

https://statmodeling.stat.columbia.edu/2022/04/05/confidence-intervals-compatability-intervals-uncertainty-intervals/

https://www.statisticshowto.com/research-methods-qualitative-research-and-quantitative-research/

https://statisticsbyjim.com/basics/cohort-study/

https://statisticsbyjim.com/hypothesis-testing/sampling-error/

https://www.r-bloggers.com/2022/04/paper-semi-markov-modeling-for-cancer-insurance/

https://www.r-bloggers.com/2022/04/teaching-data-science-in-the-cloud/

https://www.r-bloggers.com/2022/04/new-features-in-r-4-2-0/

https://www.r-bloggers.com/2022/04/bio7-3-4-released/

https://cran.r-project.org/web/packages/pipeliner/index.html

https://cran.r-project.org/web/packages/pipeliner/vignettes/Introduction.html

In this episode, I brace myself for the R release of Vigorous Calisthenics, scratch my head at Lyapunov Exponents, survey the brewing battlefield in the AI/ML Wars, and showcase the R-package 'numform'.

References:

https://journal.r-project.org/archive/2021/RJ-2021-109/RJ-2021-109.pdf

https://journal.r-project.org/archive/2021/RJ-2021-080/RJ-2021-080.pdf

https://www.jstatsoft.org/article/view/v101i12

https://www.frontiersin.org/articles/10.3389/fams.2022.818799/full

https://www.frontiersin.org/articles/10.3389/fams.2022.869999/full

https://www.frontiersin.org/articles/10.3389/fams.2022.839669/full

https://cran.r-project.org/index.html

https://pythoninsider.blogspot.com/2022/03/python-3110a6-is-available.html

https://blog.python.org/2022/03/python-3103-3911-3813-and-3713-are-now.html

https://blog.python.org/2022/03/python-3104-and-3912-are-now-available.html

https://julialang.org/blog/2022/02/10years/

https://www.statistics.com/data-literacy-the-chainsaw-case/

https://errorstatistics.com/2022/03/23/the-ai-ml-wars-explain-or-test-black-box-models/

https://statmodeling.stat.columbia.edu/2022/03/27/the-examples-you-see-in-the-textbooks-are-not-representative-of-the-sorts-of-problems-you-see-in-the-real-world/

https://statisticsbyjim.com/regression/interpret-coefficients-p-values-regression/

https://www.r-bloggers.com/2022/03/february-2022-top-40-new-cran-packages/

https://www.r-bloggers.com/2022/03/how-i-analyze-100-ggplots-at-once/

https://cran.r-project.org/web/packages/numform/numform.pdf

Trailer for the podcast Statistics Weekly.