scholarly journals Salajan's conjecture on discriminating terms in an exponential sequence

2016 ◽  
Vol 160 ◽  
pp. 646-665 ◽  
Author(s):  
Pieter Moree ◽  
Ana Zumalacárregui
Keyword(s):  
Exponential Sequence

Extending the correlation structure of exponential autoregressive–moving-average processes

1981 ◽  
Vol 18 (1) ◽  
pp. 181-189 ◽  
Author(s):  
Ed McKenzie
Keyword(s):  
Autocorrelation Function ◽  
Moving Average ◽  
Binary Sequence ◽  
Correlation Structure ◽  
Autoregressive Moving Average ◽  
Correlation Structures ◽  
Exponential Random Variables ◽  
Moving Average Processes ◽  
Negative Exponential ◽  
Exponential Sequence

Some recent constructions for the generation of dependent sequences of identically distributed negative exponential random variables with specific correlation structures are generalized. This is achieved by attributing a correlation structure to the binary sequence which controls the generation of the exponentials. The procedure causes the autocorrelation function of the exponential sequence to copy that of the binary sequence and thus be extended to include negative values and other values beyond the usual range.

Extending the correlation structure of exponential autoregressive–moving-average processes

1981 ◽  
Vol 18 (01) ◽  
pp. 181-189 ◽  
Author(s):  
Ed McKenzie
Keyword(s):  
Autocorrelation Function ◽  
Moving Average ◽  
Binary Sequence ◽  
Correlation Structure ◽  
Autoregressive Moving Average ◽  
Correlation Structures ◽  
Exponential Random Variables ◽  
Moving Average Processes ◽  
Negative Exponential ◽  
Exponential Sequence

Some recent constructions for the generation of dependent sequences of identically distributed negative exponential random variables with specific correlation structures are generalized. This is achieved by attributing a correlation structure to the binary sequence which controls the generation of the exponentials. The procedure causes the autocorrelation function of the exponential sequence to copy that of the binary sequence and thus be extended to include negative values and other values beyond the usual range.

scholarly journals Exponential Sequence in the Operational Calculus Model for the nTH-Order Forward Difference

2019 ◽  
Vol 217 (2) ◽  
pp. 35-47
Author(s):  
Hubert Wysocki
Keyword(s):  
Discrete Model ◽  
Operational Calculus ◽  
Forward Difference ◽  
Exponential Sequence

Abstract In the paper, there has been determined an exponential element in the discrete model of the non-classical Bittner operational calculus for the nth-order forward difference.

A mixed autoregressive-moving average exponential sequence and point process (EARMA 1,1)

1977 ◽  
Vol 9 (1) ◽  
pp. 87-104 ◽  
Author(s):  
P. A. Jacobs ◽  
P. A. W. Lewis
Keyword(s):  
Linear Combination ◽  
Point Process ◽  
Moving Average ◽  
Random Variables ◽  
Stationary Sequence ◽  
Autoregressive Moving Average ◽  
Marginal Distributions ◽  
Joint Distributions ◽  
Exponential Random Variables ◽  
Exponential Sequence

A stationary sequence of random variables with exponential marginal distributions and the correlation structure of an ARMA (1, 1) process is defined. The process is formed as a random linear combination of i.i.d. exponential random variables and is very simple to generate on a computer. Moments and joint distributions for the sequence are obtained, as well as limiting properties of sums of the random variables and of the point process whose intervals have the EARMA (1, 1) structure.

Unbiased Direct DGM(1,1) Model of Non-Homogeneous Exponential Sequence and its Application in Electric Load Forecasting

2013 ◽  
Vol 732-733 ◽  
pp. 972-975 ◽  
Author(s):  
De Qiang Zhou
Keyword(s):  
Load Forecasting ◽  
Grey Model ◽  
Electric Load ◽  
Traditional Methods ◽  
Recursive Solution ◽  
Forecasting Method ◽  
Application Scope ◽  
Exponential Sequence ◽  
Electric Load Forecasting

The traditional GM (1,1) has been used widely in the load forecasting, however, there are many defects in the GM (1,1). In order to overcome these defects and expand the application scope of the grey model in load forecasting, a new load forecasting method based on DDGM(1,1) is presented. First, the recursive solution of DDGM(1,1) is given. Then, based on the solution, the unbiased property for non-homogeneous exponential incremental sequence of this model is proved. It is applied to some load forecasting and is compared with the traditional GM (1,1) model.The results show that the presented forecasting method is superior obviously to traditional methods, and it can be used for the approximate non-homogeneous exponential incremental load forecasting generally.

Optimal Two-Choice Stopping on an Exponential Sequence

2006 ◽  
Vol 25 (4) ◽  
pp. 351-363
Author(s):  
Larry Goldstein ◽  
Ester Samuel-Cahn
Keyword(s):  
Exponential Sequence
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