Results 11 to 20 of about 10,496,278 (261)

On-line recognition of abnormal patterns in bivariate autocorrelated process using random forest [PDF]

, 2022
It is not uncommon that two or more related process quality characteristics are needed to be monitored simultaneously in production process for most of time.
Chen, Chunmei, Xu, Miao, Zhu, Bo, Wan, Yuwei   +3 more
core   +1 more source

Autocorrelated Error with AR(1) Process

, 2023
The autoregressive data set indicates data generated with autocorrelated error with AR ...
Isiaka Oloyede (15361816)
core   +1 more source

A Novel Scheme of Control Chart Patterns Recognition in Autocorrelated Processes

Mathematics, 2023
Control chart pattern recognition (CCPR) can quickly recognize anomalies in charts, making it an important tool for narrowing the search scope of abnormal causes.
Cang Wu, Huijuan Hou, Chunli Lei, Pan Zhang, Yongjun Du   +4 more
doaj   +1 more source

Can crude oil prices predict world tuna prices? [PDF]

Songklanakarin Journal of Science and Technology (SJST), 2020
World tuna prices exhibit substantial fluctuations over time. We studied monthly tuna and preceding crude oil prices from 1986 to 2018, using linear regression models with autoregressive and moving average (ARMA) errors.
Boonmee Lee, Mayuening Eso, Apiradee Lim, Don McNeil   +3 more
doaj   +1 more source

Nonparametric performance hypothesis testing with the information ratio

Cogent Economics & Finance, 2021
This study proposes a nonparametric bootstrap-based test to compare performances between two portfolios in terms of their information ratio. This serves as an extension to the literature that tests performance between two portfolio investment strategies ...
Jacque Bon-Isaac Aboy, Joselito Magadia
doaj   +1 more source

Rates and Rocks: Strengths and Weaknesses of Molecular Dating Methods

Frontiers in Genetics, 2020
I present here an in-depth, although non-exhaustive, review of two topics in molecular dating. Clock models, which describe the evolution of the rate of evolution, are considered first.
Stéphane Guindon
doaj   +1 more source

Subsampling Inference for the Autocorrelations of GARCH Processes*

Journal of Financial Econometrics, 2017
AbstractWe provide self-normalization for the sample autocorrelations of power GARCH(p, q) processes whose higher moments might be infinite. To validate the studentization, whose goal is to match the growth rate dependent on the index of regular variation of the process, we substantially extend existing weak-convergence results.
McElroy, Tucker, Jach, Agnieszka
openaire   +3 more sources

Monitoring the Zero-Inflated Time Series Model of Counts with Random Coefficient

Entropy, 2021
In this research, we consider monitoring mean and correlation changes from zero-inflated autocorrelated count data based on the integer-valued time series model with random survival rate.
Cong Li, Shuai Cui, Dehui Wang
doaj   +1 more source

Geometric Brownian Motion-Based Time Series Modeling Methodology for Statistical Autocorrelated Process Control: Logarithmic Return Model

International Journal of Mathematics and Mathematical Sciences, 2022
Fitting a time series model to the process data before applying a control chart to the residuals is essential to fulfill the basic assumptions of statistical process control (SPC).
Siaw Li Lee, Chin Ying Liew, Chee Khium Chen, Li Li Voon   +3 more
doaj   +1 more source

Recognition of Process Disturbances for an SPC/EPC Stochastic System Using Support Vector Machine and Artificial Neural Network Approaches

Abstract and Applied Analysis, 2014
Because of the excellent performance on monitoring and controlling an autocorrelated process, the integration of statistical process control (SPC) and engineering process control (EPC) has drawn considerable attention in recent years.
Yuehjen E. Shao
doaj   +1 more source