Forecasting with ARIMA Processes

2011 ◽  
pp. 534-536
Author(s):  
William W. S. Wei
Keyword(s):  
Arima Processes

scholarly journals Bootstrap predictive inference for ARIMA processes

2004 ◽  
Vol 25 (4) ◽  
pp. 449-465 ◽  
Author(s):  
Lorenzo Pascual ◽  
Juan Romo ◽  
Esther Ruiz
Keyword(s):  
Predictive Inference ◽  
Arima Processes

scholarly journals Experience Rating of ARIMA Processes by the Kalman Filter

1986 ◽  
Vol 16 (1) ◽  
pp. 19-31 ◽  
Author(s):  
Jukka Rantala
Keyword(s):  
Kalman Filter ◽  
Time Delay ◽  
State Space ◽  
Theoretical Approach ◽  
Space Form ◽  
The State ◽  
Experience Rating ◽  
Filter Technique ◽  
Main Emphasis ◽  
Arima Processes

AbstractThis paper deals with experience rating of claims processes of ARIMA structures. By experience rating we mean that future premiums should be only a function of past values of the claims process. The main emphasis is on demonstrating the usefulness of the control-theoretical approach in the search for optimal rating rules. Optimality is here defined to mean as smooth a flow of premiums as possible when the variation in the accumulated profit is restricted to a certain amount. First it is shown how the underlying model in its simplest form can be transformed into the state-space form. Then the Kalman filter technique is used to find the optimal rules. Also a time delay in information is taken into account. The optimal rules are illustrated by examples.

On the invertibility of fractionally differenced ARIMA processes

Biometrika ◽  
1993 ◽  
Vol 80 (3) ◽  
pp. 703-709 ◽  
Author(s):  
MITSUHIRO ODAKI
Keyword(s):  
Arima Processes

Analysis of Variety Yield Trials Using Two-Dimensional Separable ARIMA Processes

Biometrics ◽  
1996 ◽  
Vol 52 (2) ◽  
pp. 763 ◽  
Author(s):  
M. O. Grondona ◽  
J. Crossa ◽  
P. N. Fox ◽  
W. H. Pfeiffer
Keyword(s):  
Two Dimensional ◽  
Yield Trials ◽  
Arima Processes

scholarly journals A Quantitative Study on Crucial Food Supplies after the 2011 Tohoku Earthquake Based on Time Series Analysis

2020 ◽  
Vol 17 (19) ◽  
pp. 7162
Author(s):  
Xiaoxin Zhu ◽  
Yanyan Wang ◽  
David Regan ◽  
Baiqing Sun
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Quantitative Study ◽  
Moving Average ◽  
Arima Model ◽  
Tohoku Earthquake ◽  
2011 Tohoku Earthquake ◽  
The 2011 Tohoku Earthquake ◽  
Food Commodity ◽  
Arima Processes

Awareness of the requested quantity and characteristics of emergency supplies is crucial for facilitating an efficient relief operation. With the aim of focusing on the quantitative study of immediate food supplies, this article estimates the numerical autoregressive integrative moving average (ARIMA) model based on the actual data of 14 key commodities in the Sendai City of Japan during the 2011 Tohoku earthquake. Although the temporal patterns of key food commodity groups are qualitatively similar, the results show that they follow different ARIMA processes, with different autoregressive moving averages and difference order patterns. A key finding is that 3 of the 14 items are significantly related to the number of temporary residents in shelters, revealing that the relatively low number of different items makes it easier to deploy these key supplies or develop regional purchase agreements so as to promptly obtain them from distributors.

Efficient On-Line Generation of the Correlation Structure of F-ARIMA Processes

2009 ◽  
pp. 131-143
Author(s):  
Maria-Estrella Sousa-Vieira ◽  
Andrés Suárez-González ◽  
José-Carlos López-Ardao ◽  
Cándido López-García
Keyword(s):  
Correlation Structure ◽  
On Line ◽  
Arima Processes ◽  
Line Generation
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