Stationarity Verification and ARMA Model Forecasting for Quarterly Demographic Data in R
Data Ingestion and Temporal Structuring
Quarterly population shift records spanning from September 1971 to June 1993 are imported and converted into a formal time series object. The dataset is structured with a quarterly frequency to align with the observation intervals.
raw_values <- read.table("quarterly_population.dat")$V1
demog ...
Posted on Sun, 13 Sep 2026 16:13:58 +0000 by limke
Implementing Multi-step Time Series Forecasting with PyTorch Encoder-Decoder Architecture
Data Preparation
The dataset originates from a Kaggle competition involving store item demand forecasting. It contains 5 years of sales data (2013-2017) for 50 items across 10 stores, requiring predictions for the next 3 months (January-March 2018). This represents a multi-step multivariate time series problem with 500 distinct time series to f ...
Posted on Wed, 03 Jun 2026 18:16:35 +0000 by nadeemshafi9
Building and Forecasting with ARIMA Models in MATLAB: A Practical Guide
Start by loading the data from an Excel file named data.xlsx containing a single numeric column Value. The code splits the series into an 80% training segment and reserves the remainder for testing.
% Clear workspace and figures
clc; clear; close all;
% Control parameters
forceManual = 1; % 1 = use fixed ARIMA(2,1,1); 0 = auto-order selec ...
Posted on Fri, 08 May 2026 02:06:49 +0000 by juschillinnow