SwePub
Sök i LIBRIS databas

  Extended search

id:"swepub:oai:DiVA.org:hj-50689"
 

Search: id:"swepub:oai:DiVA.org:hj-50689" > Forecasting buffalo...

  • 1 of 1
  • Previous record
  • Next record
  •    To hitlist

Forecasting buffalo population of Pakistan using autoregressive integrated moving average (ARIMA) time series models

Qasim, Muhammad (author)
Jönköping University,IHH, Statistik
Amin, M. (author)
Department of Statistics, University of Sargodha, Pakistan
Akram, M. N. (author)
Department of Statistics, University of Sargodha, Pakistan
show more...
Omer, Talha (author)
Jönköping University,IHH, Statistik
Hussain, F. (author)
Department of Animal Nutrition, University of Veterinary and Animal Sciences, Lahore, Pakistan
show less...
 (creator_code:org_t)
Giunti, 2019
2019
English.
In: Proceedings of the Pakistan Academy of Sciences: Part A. - : Giunti. - 2518-4245 .- 2518-4253. ; 56:3, s. 11-20
  • Journal article (peer-reviewed)
Abstract Subject headings
Close  
  • Livestock plays a vital role in Pakistan’s economy. Buffalo is the primary source of milk and meat, which is a basic need for human health. So, there is a need to forecast the buffalo population of Pakistan. The main objective of the current study is to determine an appropriate empirical model for forecasting buffalo population of Pakistan to assess its future trend up to the year 2030. We apply different Autoregressive Integrated Moving Average (ARIMA) models on the buffalo population-based on fifty-years’ time-series dataset. Different model selection criteria are used to test the reliability of the ARIMA models. Based on these criteria, we perceive that ARIMA (1, 0, 0) is a more suitable model. Moreover, we also test the fitted model assumptions, such as normality and independence, to find out more accurate forecasted values. This study revealed that the buffalo population expected to increase 30% up to the year 2030 under the assumption that there is no irregular trend can be encountered during forecasted years.

Subject headings

NATURVETENSKAP  -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
NATURAL SCIENCES  -- Mathematics -- Probability Theory and Statistics (hsv//eng)

Keyword

Autoregressive Integrated Moving Average (ARIMA)
Buffalo
Estimated Root Mean Square Error (ERMSE)
Time Series Model

Publication and Content Type

ref (subject category)
art (subject category)

Find in a library

To the university's database

  • 1 of 1
  • Previous record
  • Next record
  •    To hitlist

Find more in SwePub

By the author/editor
Qasim, Muhammad
Amin, M.
Akram, M. N.
Omer, Talha
Hussain, F.
About the subject
NATURAL SCIENCES
NATURAL SCIENCES
and Mathematics
and Probability Theo ...
Articles in the publication
Proceedings of t ...
By the university
Jönköping University

Search outside SwePub

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Close

Copy and save the link in order to return to this view