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Parameters Estimate of Autoregressive Moving Average and Autoregressive Integrated Moving Average Models and Compare Their Ability for Inflow Forecasting [PDF]
In this study the ability of Autoregressive Moving Average (ARMA) and Autoregressive Integrated Moving Average (ARIMA) models in forecasting the monthly inflow of Dez dam reservoir located in Teleh Zang station in Dez dam upstream i s estimated. ARIMA model has found a widespread application in many practical sciences. In addition, dam reservoir inflow
Mohammad Valipour+2 more
openaire +2 more sources
Abstract The valuation effects on international investment position induced by the exchange rate volatility are not uniform or easily manageable in small and vulnerable economies when compared with larger developing or developed countries. To investigate the underlying dynamics, we developed a foreign currency exposure index over the period 2006–2019 ...
Devendra Kumar Jain+4 more
wiley +1 more source
Abstract Marine Protected Areas (MPAs) are increasingly used as a management and conservation strategy. However, the effects of MPA implementation (i.e. restrictions on extractive use) on recreational fishers' spatial behaviour are often not considered.
Haley K. Fox+2 more
wiley +1 more source
AUTOREGRESSIVE INTEGRATED MOVING AVERAGE FOR COCOA PRODUCTION IN SULAWESI ISLAND 2021-2030
Agribusiness Cocoa on the island of Sulawesi is very supported by the availability of land plantations to produce production even bigger cocoa with management plant and processing seed good cocoa _ thus producing quality cocoa beans.
Nixia Tenriawaru+6 more
doaj +1 more source
Bayesian time‐varying autoregressive models of COVID‐19 epidemics
Abstract The COVID‐19 pandemic has highlighted the importance of reliable statistical models which, based on the available data, can provide accurate forecasts and impact analysis of alternative policy measures. Here we propose Bayesian time‐dependent Poisson autoregressive models that include time‐varying coefficients to estimate the effect of policy ...
Paolo Giudici+2 more
wiley +1 more source
Forecasting is the process of making predictions based on past and present data, with the most common method being trend analysis. Forecasting models are becoming increasingly crucial in uncovering the intricate linkages between large amounts of ...
Teg Alam, A. Alarjani
semanticscholar +1 more source
Metode Autoregressive Integrated Moving Average untuk Meramalkan Penjualan
Kondisi sales performance dipengaruhi oleh sales budget (anggaran penjualan) yang telah ditetapkan di periode sebelumnya. Penetapan sales budget berdasarkan pada hasil ramalan penjualan (sales forecast) yang sudah dianalisa sebelumnya. Penetapan sales forecast di PT.
Indri Astuti, Emmelia Tan
openaire +3 more sources
Abstract Background Ambulatory assessments offer opportunities to study physical activity level (PAL) and affect at the group and person‐level. We examined bidirectional associations between PAL and affect in a 3‐h timeframe and evaluated whether associations differ between people with and without current or remitted depression/anxiety.
Sonia Difrancesco+5 more
wiley +1 more source
SARIMA: A Seasonal Autoregressive Integrated Moving Average Model for Crime Analysis in Saudi Arabia
Crimes have clearly had a detrimental impact on a nation’s development, prosperity, reputation, and economy. The issue of crime has become one of the most pressing concerns in societies, thus reducing the crime rate has become an increasingly critical ...
Talal H. Noor+5 more
semanticscholar +1 more source
An Evaluation of ARFIMA (Autoregressive Fractional Integral Moving Average) Programs [PDF]
Strong coupling between values at different times that exhibit properties of long range dependence, non-stationary, spiky signals cannot be processed by the conventional time series analysis. The autoregressive fractional integral moving average (ARFIMA) model, a fractional order signal processing technique, is the generalization of the conventional ...
Kai Liu, YangQuan Chen, Xi Zhang
openaire +2 more sources