Results 101 to 110 of about 10,496,278 (261)

The Accuracy Smoothness Dilemma in Prediction: A Novel Multivariate M‐SSA Forecast Approach

Journal of Time Series Analysis, EarlyView.
ABSTRACT Forecasting presents a complex estimation challenge, as it involves balancing multiple, often conflicting, priorities and objectives. Conventional forecast optimization methods typically emphasize a single metric, such as minimizing the mean squared error (MSE), which may neglect other crucial aspects of predictive performance. To address this
Marc Wildi
wiley   +1 more source

Monoalcohol-Directed Shape Control in a Surfactant-Free Gold Nanoplate Synthesis. [PDF]

Small Methods
Surfactant‐free monoalcohol syntheses are advantageous in that they yield colloidal nanostructures that are free of persistent shape‐directing agents but at the expense of realizing only spherically‐shaped nanoparticles. In this work, this limitation is overcome using a low‐complexity light‐driven synthetic protocol yielding periodic arrays of gold ...
Nieukirk BD, Zhang S, Tang R, Xu K, Rosenberger MR, Hughes RA, Fichthorn KA, Neretina S.   +7 more
europepmc   +2 more sources

The Estimation of an Autocorrelation Parameter of a Gaussian Vector Process

Journal of the Royal Statistical Society Series B: Statistical Methodology, 1979
Summary A procedure based on differences is used to yield an estimator of an unknown parameter occurring in the autocorrelation structure of a stationary Gaussian vector process. Various properties of the estimator including its existence, consistency and asymptotic normality are shown.
openaire   +2 more sources

Sparse Causal Dynamic Linear Regression

Journal of Time Series Analysis, EarlyView.
ABSTRACT We develop a sparse causal dynamic regression framework for long multivariate time series. With very long time series, the potentially large number of lags and leads in a dynamic regression model often makes time‐domain estimation numerically unstable or intractable.
Rui Huang, Kung‐Sik Chan
wiley   +1 more source

Change detection in autocorrelated processes [PDF]

, 1999
grantor: University of TorontoThe problem of change detection is about quick detection of a change in a dynamic system or process at a low rate of false alarm by sequentially observing the system or process.
Yang, Jiangbin
core   +2 more sources

Max-EWMA chart for autocorrelated processes (MEWMAP chart) [PDF]

, 2007
This paper proposes an exponentially weighted moving average (EWMA) control chart that is capable of detecting changes in both process mean and standard deviation for autocorrelated data (referred to as the Maximum Exponentially Weighted Moving Average ...
Thaga, K., Yadavalli, Venkata S. Sarma
core   +1 more source

Real and Apparent Deviations From Rational Choice

Kyklos, EarlyView.
ABSTRACT This paper offers a taxonomy of real and apparent deviations from rationality. The taxonomy is based on three axes of divides—whereas the axes are successive refinements. The outermost‐axis divide delineates “anxiety‐based choices” from “anxiety‐free choices.” Anxiety‐based choices are real deviations such as the Allais and Ellsberg paradoxes ...
Elias L. Khalil
wiley   +1 more source

Output Gap Uncertainty, Sovereign Risk Premia and the Contingent Importance of the Bond Vigilantes

Metroeconomica, EarlyView.
ABSTRACT This paper investigates the implications of output gap uncertainty for the conduct of fiscal policy using a small‐scale macroeconomic model with boundedly rational agents. Specifically, agents use an adaptive updating mechanism to approximate the unobservable potential output that suffers, similarly to the Hodrick and Prescott (1997) filter ...
Christian R. Proaño, Jonas Dix
wiley   +1 more source

Multivariate Statistical Process Control Charts: An Overview [PDF]

In this paper we discuss the basic procedures for the implementation of multivariate statistical process control via control charting. Furthermore, we review multivariate extensions for all kinds of univariate control charts, such as multivariate ...
Bersimis, Sotiris, Panaretos, John, Psarakis, Stelios   +2 more
core  

Cluster analysis for autocorrelated and cyclic chemical process data

, 2007
A clustering algorithm based on principal components analysis (PCA) is proposed for clustering autocorrelated and cyclic data sets typical of continuous chemical processes.
Romagnoli, José A., Palazoglu, Ahmet, Beaver, Scott   +2 more
core   +1 more source