Time Series Outlier Analysis of Tea Price Data
Issue:
Volume 2, Issue 1, January 2013
Pages:
1-6
Published:
10 January 2013
DOI:
10.11648/j.ajtas.20130201.11
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Abstract: In this article Autoregressive Integrated Moving Average (ARIMA) models were fitted and outliers are identified for the auction price of tea in three regions- North India, South India and All India. The ARIMA models with seasonal differencing are found to be quite appropriate for the data. The region specific dynamics are distinctly assessed based on the autocorrelation functions. Further we are concerned with outliers in time series with two special cases, additive outlier (AO) and innovational outlier (IO).These outliers have been detected using two recent methods and conclusions drawn based on the data pertaining to the three regions. The reason for these types of outliers in the tea price have been further identified pointing towards the factors of environmental, weather conditions, pest attacks etc.
Abstract: In this article Autoregressive Integrated Moving Average (ARIMA) models were fitted and outliers are identified for the auction price of tea in three regions- North India, South India and All India. The ARIMA models with seasonal differencing are found to be quite appropriate for the data. The region specific dynamics are distinctly assessed based ...
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Comparative Analysis of Bayesian Control Chart Estimation and Conventional Multivariate Control Chart
Johnson Ademola Adewara1,
J. Ademola,
Ogundeji K. Rotimi
Issue:
Volume 2, Issue 1, January 2013
Pages:
7-11
Published:
10 January 2013
DOI:
10.11648/j.ajtas.20130201.12
Downloads:
Views:
Abstract: Bayesian model or Beta-binomial conjugate using Bayesian sequential estimation method to estimate the proportion of different age groups is compared with the conventional multivariate control chart method. The parameters for the techniques were derived and applied. The result shows that the patients between the ages of 15-44 in 2009 and 44-64 and 64 and above in 2011 are out of control. This implies the Bayesian sequential estimation method is very efficient to notice any small shift that occurs among patients that make use of the hospital. Also the bracket mentioned above was very high among the people that used the hospital compared to others. The result of 2011shows that there was a high shift in the ages of the patients that attended the hospital for the ages between 44-64 and 64 and above respectively.
Abstract: Bayesian model or Beta-binomial conjugate using Bayesian sequential estimation method to estimate the proportion of different age groups is compared with the conventional multivariate control chart method. The parameters for the techniques were derived and applied. The result shows that the patients between the ages of 15-44 in 2009 and 44-64 and 6...
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