In a previous post I explained CAGR-based forecasting. CAGR-based forecasting is a very simple forecasting method which is often applied in industry, e.g. for forecasting sales and production output. Simple forecasting models have benefits. They are easy to understand and easy […]

## CAGR-based forecasting, using OICA production data (in R)

## Testing “coronavirus”, a package in R for accessing data from J.H. university

## OICA production output statistics for automotive industry (R analysis)

## EPA data analyzed in R for visualizing US powertrain shares

## Analyzing used car prices with German ebay postings from 2016 (kaggle, R)

## Public fuel consumption data from data.gov, for Montgomery county – visualized in R

## Plotting carsalesbase total annual US vehicle sales data (using R)

## VDA time series data on German automotive industry, analyzed in R

## Time series of hourly earnings in US automotive industry (bls.gov), analyzed in R

## Solving linear problem with fuzzy constraints by sampling beta with FuzzyLP in R

## Linear optimization with fuzzy constraints conducted in R with FuzzyLP

## Simple linear problem with FuzzyLP, using crispLP and basic simplex

## Comparing different German transport sectors by volume, using OECD data in R

Based on my recent OECD-package related post (http://www.supplychaindataanalytics.com/oecd-package-interface-in-r-reading-german-freight-transport-data-from-oecd-directly-in-r/) I extend my recenet analysis of German transport volume development by comparing different inland freight categories in a ggplot-chart. The data, again, i querried using the OECD-package in R. From the previous […]