Skip to content
#

statistical-methods

Star

Here are 111 public repositories matching this topic...

Language: All
Filter by language
All 111 Jupyter Notebook 24 R 22 Python 15 HTML 11 JavaScript 5 MATLAB 5 Java 4 TeX 4 C 3 C++ 3
Sort: Best match
Sort options
Best match Most stars Fewest stars Most forks Fewest forks Recently updated Least recently updated

jkriege2 / JKQtPlotter

Star

an extensive Qt5 Plotter framework (including a feature-richt plotter widget, a speed-optimized, but limited variant and a LaTeX equation renderer!), written fully in C/C++ and without external dependencies

qt charting-library plot statistical-methods qt5 scientific-visualization barchart graphics-programming graphing plotting qt-gui charting qt5-gui qt-libraries latex-parser qt-widgets boxplots violinplot qt5-widgets plotting-library
  • Updated Oct 27, 2020
  • C++
pf

tbrown122387 / pf

Star
Open

Split filter() into two functions

tbrown122387
tbrown122387 commented May 1, 2020

Consider rewriting filter() so that it makes use of two public functions: one to perform mutation and rewrighting, and the other to perform resampling. This added level of control would be useful for latency-sensitive applications that only need to make use of the results from the first stage. After that, resampling could be performed while there is plenty of downtime.

A challenge would be to e

Read more
good first issue

devildances / DataScience_in_small_notes

Star

Some little notes from the author for everyone who wants to know or learn about the process that a data scientist must do from the beginning of data collection to making predictions with a model that has been built. These notes are based on the knowledge that the authors have learned and implemented. Enjoy it!

data-science exploratory-data-analysis statistical-methods data-visualization python3 statistical-analysis supervised-learning data-analysis unsupervised-learning cleaning-data
  • Updated Sep 29, 2020
  • Jupyter Notebook

inboxpraveen / Introduction_to_Statistical_learning_with_Application_in_R_LAB

Star

This repository consists of all the LAB exercise from "INTRODUCTION TO STATISTICAL LEARNING WITH APPLICATION IN R" by by Daniela Witten, Gareth James, Robert Tibshirani, and Trevor Hastie. All the Datasets and Chapterwise notes are also present.

learning application r statistics code lab statistical-learning statistical-methods statistical-analysis statistical-inference statistical introduction statistical-data introduction-to-r
  • Updated Nov 7, 2018
  • HTML

akshitvjain / product-sales-forecasting

Star

Forecasted product sales using time series models such as Holt-Winters, SARIMA and causal methods, e.g. Regression. Evaluated performance of models using forecasting metrics such as, MAE, RMSE, MAPE and concluded that Linear Regression model produced the best MAPE in comparison to other models

machine-learning linear-regression machine-learning-algorithms statistical-methods regression time-series-analysis arima-model sales-forecasting statistical-modeling exponential-smoothing holt-winters time-series-decomposition sarima ets-model
  • Updated Dec 30, 2019
  • Jupyter Notebook

Improve this page

Add a description, image, and links to the statistical-methods topic page so that developers can more easily learn about it.

Curate this topic

Add this topic to your repo

To associate your repository with the statistical-methods topic, visit your repo's landing page and select "manage topics."

Learn more

You can’t perform that action at this time.