OpenAI announced today that it is releasing a new family of artificial intelligence models optimized to excel at coding, as it ramps up efforts to fend off increasingly stiff competition from ...

The paper investigated the problem of restoring missing values in time series data analysis. The aim of this study was to advance the imputation of missing values for some autoregressive moving ...

Abstract: Fault detection in mechatronic transmissions is particularly challenging due to the nonstationary nature of monitoring signals arising from complex operating conditions, coupled with the ...

Creating a monthly budgeting and forecasting model in Excel is a crucial skill for effective financial planning and management. This step-by-step guide by Kenji will walk you through the process of ...

1 Department of Statistics, Federal College of Animals Health and Production Technology, Ibadan, Nigeria. 2 New York Institute of Technology, New York, USA. A comparative analysis of deep learning ...

We study solutions to the stochastic fixed point equation $X\stackrel{d}{=}AX+B$ when the coefficients are nonnegative and $B$ is an “inverse exponential decay ...

Cutting corners: Spreadsheets are a staple of so many jobs and business fields that it is almost impossible to quantify their economic value. People adept with this tool are in high demand and often ...

Timeseries prediction using both linear ARMA models and non-linear models ︎ Timeseries Course ︎ 2023-2024 ︎ School of Electrical and Computer Engineering @ Aristotle University of Thessaloniki (AUTh) ...

In this lesson, you'll use your knowledge of the autoregressive (AR) and moving average (MA) models, along with the statsmodels library to model time series data.

Two vital signs including heartbeat and respiratory rate are monitored in this work under two constraint situations; namely noise disturbance and intermittent observations. The existing scheme for ...