Identification of the Demand Curve and Forecasts in Subsequent Periods Using the Metropolis-Hastings Algorithm
Artykuł w czasopiśmie
MNiSW
100
Lista 2021
Status: | |
Autorzy: | Gołąbek Łukasz, Gauda Konrad, Żuk Krzysztof, Kozłowski Edward |
Dyscypliny: | |
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Rok wydania: | 2021 |
Wersja dokumentu: | Drukowana | Elektroniczna |
Język: | angielski |
Numer czasopisma: | Special Issue 2 |
Wolumen/Tom: | 24 |
Strony: | 523 - 533 |
Efekt badań statutowych | NIE |
Materiał konferencyjny: | NIE |
Publikacja OA: | TAK |
Licencja: | |
Sposób udostępnienia: | Otwarte czasopismo |
Wersja tekstu: | Ostateczna wersja opublikowana |
Czas opublikowania: | W momencie opublikowania |
Data opublikowania w OA: | 30 czerwca 2021 |
Abstrakty: | angielski |
Purpose: The main purpose of the article is to identify the demand curve and to forecast demand in subsequent periods using the Metropolis-Hastings algorithm. Design/Methodology/Approach: The Metropolis-Hastings algorithm belonging to the Markov Chain Monte Carlo was used to identify the demand curve and to forecast the demand in subsequent periods. This method consists in generating (drawing) a sample in accordance with the modified distribution and the possibility of rejecting a new sample in case of insufficient improvement of the quality index. Findings: The results of the conducted research indicate that the presented solution of generating a sample in accordance with the modified distribution and the possibility of rejecting a new sample in the event of insufficient improvement of the quality index is effective in identifying and forecasting the demand. Practical Implications: The algorithm presented in the article can be used to forecast stays taking into account the product life curve. Originality/Value: A novelty is the use of the Metropolis-Hastings algorithm to identify the demand curve and the forecast of demand in subsequent periods to determine the strategy of long-term products by analyzing the sales volume of the product. |