Results 261 to 270 of about 289,013 (304)

Serial Correlation in a Simple Dam Processs

Operations Research, 1973
This paper deals with a dam model similar to one due to P. A. P. Moran. It assumes that both the inflow and release of water are exponentially distributed random variables and studies the dam during its steady state. It derives the serial correlation in the sequence of water levels and compares it with previous results for a corresponding queuing ...
openaire   +2 more sources

An automatic Portmanteau test for serial correlation

Journal of Econometrics, 2009
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Escanciano, J. Carlos, Lobato, Ignacio N.   +1 more
openaire   +2 more sources

SERIAL CORRELATION IN MULTIREGIONAL MIGRATION MODELS*

Journal of Regional Science, 1990
ABSTRACTIn this paper, we outline the specification and estimation of a time series of multiregional net‐migration equations subject to first‐order serial correlation. We show that the necessary nonstochastic adding‐up constraint, which requires that net migration in the system sum to zero, imposes restrictions on the serial‐correlation coefficients ...
D K, Foot, W J, Milne
openaire   +2 more sources

THE APPROXIMATE DISTRIBUTION OF SERIAL CORRELATION COEFFICIENTS

Biometrika, 1956
Hotelling's suggestion of a 'circular' definition for the serial correlation coefficient was followed by considerable progress in the distribution theory of such modified statistics by R. L. Anderson (1942), Koopmans (1942), Dixon (1944), Madow (1945) and others.
openaire   +1 more source

with Serially Correlated Inflows

Technometrics, 1963
This paper outlines a method of extending Moran's theory of finite reservoirs so as to take account of serial correlation in the sequence of inflows. The technique developed is to assume that the structure of this sequence can be adequately approximated by a Markov chain, and then to work with the bivariate Markov process describing the joint ...
openaire   +1 more source

Heteroscedasticity and serial correlation

1986
There are many situations occurring in practice when the simple structure of random variation assumed in (1.1) does not hold; examples will be given below. Suppose that instead of (1.1) we have $$\left. {{}_{V\left( Y \right)\, = \,V{\sigma ^2},}^{E\left( Y \right)\, = \,a\theta ,}} \right\}$$ (9.1) where V is a known n × n positive definite ...
G. Barrie Wetherill, P. Duncombe, M. Kenward, J. Köllerström, S. R. Paul, B. J. Vowden   +5 more
openaire   +1 more source

Serial correlation of detrended time series

Physical Review E, 2008
A preliminary essential procedure in time series analysis is the separation of the deterministic component from the random one. If the signal is the result of superposing a noise over a deterministic trend, then the first one must estimate and remove the trend from the signal to obtain an estimation of the stationary random component.
Călin, Vamoş, Maria, Crăciun
openaire   +2 more sources

Multiple Bi-Serial and Multiple Point Bi-Serial Correlation

Psychometrika, 1947
Normal equations, using data in various forms, are presented for securing the regression weights for prediction of a dichotomized criterion, and a simplified equation for the estimation of the multiple bi-serial or multiple point bi-serial, depending upon the proper assumption as to the nature of the distribution of the criterion, on the basis of these
openaire   +2 more sources

ASYMPTOTIC EXPANSIONS FOR THE DISTRIBUTIONS OF SERIAL CORRELATIONS

Journal of Time Series Analysis, 1987
Abstract. Let X1, …, Xn be a random sample from a population with a distribution function F and let E(X1) = 0, E(X12) < ∞. Let r1=Σt=1n‐1XtXt+1/Σt=1n‐1(Xt2+Xt+12). We derive a proper Edgeworth type expansion for the sampling distribution of r1 under the assumption that F is a mixture of Gaussian distributions of one of two given types.
openaire   +1 more source

A likelihood test for multivariate serial correlation

Biometrika, 1980
SUMMARY A procedure is proposed for testing the hypothesis that a sequence of vector-valued random variables is mutually independent. The test is based on the likelihood criterion for first-order autocorrelation assuming a multivariate normal distribution, is simple computationally, and provides a multivariate generalization of the serial correlation ...
openaire   +1 more source