A Monte-Carlo weighted moving average procedure was developed for smoothing time series data. The applicability of the method was demonstrated by using two economic time series data set to make comparison with the models, classified as k-th simple moving average, simple exponential weighted moving average, k-th weighted moving average and k-th exponential weighted moving average processes. In terms of the mean square error and mean absolute error, the Monte-Carlo weighted moving average (MC-WMA) process outperformed the other models.Keywords: Monte-Carlo weighted moving average, Weighted moving average, Exponential weighted moving average Mean square error, Mean absolute erro
The exponentially weighted moving average (EWMA) is a well-known and popular statistic used for smoo...
This thesis focuses on time series analysis usikng methods based on moving averages, especially the ...
The object of the present study is to propose a forecasting model for a nonstationary stochastic rea...
In this paper, we consider a class of weighted moving average models called the k-th moving average,...
Pharmacy is a business-oriented business which directly sells medicines to consumers. In ensuring th...
This research aimed to propose a newly-mixed control chart called the Exponentially Weighted Moving ...
Includes bibliographical references (pages [52]-53)This study designs an exponentially weighted movi...
Simple (equally weighted) moving averages are frequently used to estimate the current level of a tim...
In this manuscript, a new hybrid exponentially weighted moving average chart using the exponential d...
Smoothing time series allows removing noise. Moving averages are used in finance to smooth stock pri...
A forecasting model for a nonstationary stochastic realization is proposed based on modifying a give...
This paper shows how to modify the smoothing constant for use in an Exponentially Weighted Moving Av...
Moving Average is one of widely known technical indicator used to predict the future data in time se...
Moving Average is one of widely known technical indicator used to predict the future data in time se...
In 2016, a time series forecasting technique which combined the weighting factor calculation formula...
The exponentially weighted moving average (EWMA) is a well-known and popular statistic used for smoo...
This thesis focuses on time series analysis usikng methods based on moving averages, especially the ...
The object of the present study is to propose a forecasting model for a nonstationary stochastic rea...
In this paper, we consider a class of weighted moving average models called the k-th moving average,...
Pharmacy is a business-oriented business which directly sells medicines to consumers. In ensuring th...
This research aimed to propose a newly-mixed control chart called the Exponentially Weighted Moving ...
Includes bibliographical references (pages [52]-53)This study designs an exponentially weighted movi...
Simple (equally weighted) moving averages are frequently used to estimate the current level of a tim...
In this manuscript, a new hybrid exponentially weighted moving average chart using the exponential d...
Smoothing time series allows removing noise. Moving averages are used in finance to smooth stock pri...
A forecasting model for a nonstationary stochastic realization is proposed based on modifying a give...
This paper shows how to modify the smoothing constant for use in an Exponentially Weighted Moving Av...
Moving Average is one of widely known technical indicator used to predict the future data in time se...
Moving Average is one of widely known technical indicator used to predict the future data in time se...
In 2016, a time series forecasting technique which combined the weighting factor calculation formula...
The exponentially weighted moving average (EWMA) is a well-known and popular statistic used for smoo...
This thesis focuses on time series analysis usikng methods based on moving averages, especially the ...
The object of the present study is to propose a forecasting model for a nonstationary stochastic rea...