NDLI: The computing problem in the analysis of non-stochastic time series using an auto-regression model

Please wait, while we are loading the content...

On rational function approximations to the exponential function with application to the practical solution of linear differential difference equations with constant coefficients

On the method of minimum (or "best") approximation and the method of least nth powers

On Bernoulli's method for solving algebraic equations, II

The down-hill method of solving a polynomial equation

“Simple” approximations

On the design of business systems for computers

Technical market analysis using a computer

Small business applications using a UNIVAC Computing Center

Estimating the truncation error with a modified runge-kutta method

On the overall stability and convergence of single-step integration schemes for ordinary differential equations

Generated error in the solution of certain linear difference equations

Evaluation of incomplete elliptic integrals by gaussian integration

Programming of the method of characteristics for axisymmetric flow

A method of computing shock waves

A variational approximation for sturm-liouville problems

Simulation techniques for the test and evaluation of real-time computer programs

Automatic data-recording in real-time control systems

A system for general-purpose analog-digital computation

Sampling frequency of digital servomechanisms

Progress in simulation of valve train dynamics

Servomultiplier error $study^{1}$

The refuge relay function generator

A transistor operational d.c. amplifier

The computing problem in the analysis of non-stochastic time series using an auto-regression model

Sorting on a multiple magnetic tape unit

Automatic Digital Encoding System, II (ADES II)

A mathematical language compiler

Computer programming and coding at the high school level

A proposal for training youngsters in digital computing techniques

On the recognition of information with a digital computer

A learning process suitable for mechanization

Circuit realization of binary functions using threshold devices

Designing computer circuits with a computer

The design of synchronizing buffers for collecting and distribution digital data

Latin squares and magnetic-core matrix storage

Characteristic values of arbitrary matrices

An efficient form of inverse for sparse matrices

The method of reduced matrices for a general transportation problem1

The Tarski decision procedure

Leakage error in a semi-discrete analog of the heat equation

On partial differential equations with irregular boundaries

Optimum recurrence formulas for a fourth order parabolic partial differential equation

On rational function approximations to the exponential function with application to the practical solution of linear differential difference equation with constant coefficients

The computing problem in the analysis of non-stochastic time series using an auto-regression model

Content Provider	ACM Digital Library
Author	Szatrowski, Z.
Abstract	Autoregression models have been used in the analysis of stochastic time series or time series which have been assumed to be stochastic after some kind of adjustment. In economics, meteorology, biology, etc., the time series data are non-stochastic and the problem is to estimate, in some way, the periodic, the trend, the cyclical and the random components. In business and economic data the periodic component may be the seasonal pattern or regular weekly fluctuation. Quite frequently, in such series, the pattern of the periodic movement depends on the recent history of the series. Also, these periodic patterns may change over a period of time. Existing methods for the analysis of the above are successive approximation methods. For example, the long term cyclical and trend movements are approximated by moving averages and removed from the series by subtraction. From the adjusted data the periodic movements are estimated by some averaging process and the time series of such estimates may be further examined for changes in the pattern of the periodic movement. Usually no estimates of statistical significance or reliability are made. Even though the inadequacies of the above methods were known, more adequate and more comprehensive models were not used because of the computing difficulties.
Starting Page	102
Ending Page	105
Page Count	4
File Format	PDF
DOI	10.1145/800258.808960
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	1956-01-01
Publisher Place	New York
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Bayesian Time Series: Models and Computations for the Analysis of Time Series in the Physical Sciences (1995)

Fuzzy auto-regressive model and its applications

Time-Domain Methods for Diffusive Transport in Soft Matter

Nonlinear mechanical system identification method using auto-regression time series analysis

Comparative analysis of time series techniques ARIMA and ANFIS to forecast Wimax traffic

The application of wavelet and time series analysis in quality monitoring of digital signal

Confidence bands in nonparametric time series regression (2008).

Artificial neural network and non-linear regression: a comparative study.

AN EXACT TEST FOR A STOCHASTIC COEFFICIENT IN A TIME SERIES REGRESSION MODEL

The computing problem in the analysis of non-stochastic time series using an auto-regression model

Similar Documents

Bayesian Time Series: Models and Computations for the Analysis of Time Series in the Physical Sciences (1995)

Fuzzy auto-regressive model and its applications

Time-Domain Methods for Diffusive Transport in Soft Matter

Nonlinear mechanical system identification method using auto-regression time series analysis

Comparative analysis of time series techniques ARIMA and ANFIS to forecast Wimax traffic

The application of wavelet and time series analysis in quality monitoring of digital signal

Confidence bands in nonparametric time series regression (2008).

Artificial neural network and non-linear regression: a comparative study.

AN EXACT TEST FOR A STOCHASTIC COEFFICIENT IN A TIME SERIES REGRESSION MODEL

The computing problem in the analysis of non-stochastic time series using an auto-regression model