Results 161 to 170 of about 3,061,654 (200)
Some of the next articles are maybe not open access.
Econometric Theory, 2006
Summary: This paper introduces a new test statistic for the null hypothesis of short memory against long memory alternatives. The novelty of our statistic is that it is based on only high-order sample autocovariances and by construction eliminates the effects of nuisance parameters typically induced by short memory autocorrelation.
Harris, D, McCabe, B, Leybourne, S
openaire +3 more sources
Summary: This paper introduces a new test statistic for the null hypothesis of short memory against long memory alternatives. The novelty of our statistic is that it is based on only high-order sample autocovariances and by construction eliminates the effects of nuisance parameters typically induced by short memory autocorrelation.
Harris, D, McCabe, B, Leybourne, S
openaire +3 more sources
Neural Computation, 1997
Learning to store information over extended time intervals by recurrent backpropagation takes a very long time, mostly because of insufficient, decaying error backflow. We briefly review Hochreiter's (1991) analysis of this problem, then address it by introducing a novel, efficient, gradient based method called long short-term memory (LSTM). Truncating
Hochreiter, Sepp, Schmidhuber, Jürgen
openaire +3 more sources
Learning to store information over extended time intervals by recurrent backpropagation takes a very long time, mostly because of insufficient, decaying error backflow. We briefly review Hochreiter's (1991) analysis of this problem, then address it by introducing a novel, efficient, gradient based method called long short-term memory (LSTM). Truncating
Hochreiter, Sepp, Schmidhuber, Jürgen
openaire +3 more sources
The hippocampus and long-term memory
Cognitive Neuroscience, 2022This special issue of Cognitive Neuroscience focuses on the roles of the hippocampus during long-term memory. A discussion paper by Tallman, Clark, and Smith (this issue) found that functional connectivity of the hippocampus with the parahippocampal cortex and fusiform gyrus decreased with memory age, providing support for systems consolidation ...
openaire +2 more sources
TESTING FOR LONG MEMORY IN VOLATILITY
Econometric Theory, 2002We consider the asymptotic behavior of log-periodogram regression estimators of the memory parameter in long-memory stochastic volatility models, under the null hypothesis of short memory in volatility. We show that in this situation, if the periodogram is computed from the log squared returns, then the estimator is asymptotically normal, with the
Hurvich, Clifford M., Soulier, Philippe
openaire +1 more source
Do long-memory models have long memory?
International Journal of Forecasting, 2000Abstract This paper examines the predictability memory of fractionally integrated ARMA processes. Very long memory is found for positively fractionally integrated processes with large positive AR parameters. However, negative AR parameters absorb, to a great extent, the memory generated by a positive fractional difference.
openaire +1 more source
Long Memory with Seasonal Effects
Statistical Inference for Stochastic Processes, 2000The paper is a review of some results on long memory processes having hyperbolically damped oscillating covariance function. There are two parametric families of seasonal long memory models proposed by Granger. One of them (FARMA models) is obtained by filtering a white noise using the transfer function \((1-z)^d\), the other is based on aggregation of
Oppenheim, G. +2 more
openaire +1 more source
2008
Long memory models are statistical models that describe strong correlation or dependence across time series data. This kind of phenomenon is often referred to as “long memory” or “long-range dependence.” It refers to persisting correlation between distant observations in a time series. For scalar time series observed at equal intervals of time that are
openaire +1 more source
Long memory models are statistical models that describe strong correlation or dependence across time series data. This kind of phenomenon is often referred to as “long memory” or “long-range dependence.” It refers to persisting correlation between distant observations in a time series. For scalar time series observed at equal intervals of time that are
openaire +1 more source
2013
My last meeting with Da Ruan was in Spring 2011 at Tsinghua University, where we were talking about his plan for the next visit to us in Fall 2011 for a bit longer stay on campus to have more chats and thoughts on some future research ideas. As a matter of fact, this last meeting had been one of many gatherings with him during 23 years since we first ...
openaire +1 more source
My last meeting with Da Ruan was in Spring 2011 at Tsinghua University, where we were talking about his plan for the next visit to us in Fall 2011 for a bit longer stay on campus to have more chats and thoughts on some future research ideas. As a matter of fact, this last meeting had been one of many gatherings with him during 23 years since we first ...
openaire +1 more source
Long memory and stochastic trend
Statistics & Probability Letters, 2003zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Leipus, Remigijus, Viano, Marie-Claude
openaire +2 more sources