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View article: Distance‐weighted discrimination of face images for gender classification
Distance‐weighted discrimination of face images for gender classification Open
We illustrate the advantages of distance‐weighted discrimination for classification and feature extraction in a high‐dimension low sample size (HDLSS) situation. The HDLSS context is a gender classification problem of face images in which …
View article: Modelling time series with multiple seasonalities: an application to hourly NO$${_2}$$ pollution levels
Modelling time series with multiple seasonalities: an application to hourly NO$${_2}$$ pollution levels Open
Multiple seasonalities often appear in high-frequency data such as hourly measurements of air pollutants. These multiple seasonalities are due to human activities, with daily and weekly cycles, and climatic conditions, with daily and annua…
View article: Selecting the number of factors in multi‐variate time series
Selecting the number of factors in multi‐variate time series Open
How many factors are there? It is a critical question that researchers and practitioners deal with when estimating factor models. We proposed a new eigenvalue ratio criterion for the number of factors in static approximate factor models. I…
View article: outliers.ts.oga: Efficient Outlier Detection for Large Time Series Databases
outliers.ts.oga: Efficient Outlier Detection for Large Time Series Databases Open
Programs for detecting and cleaning outliers in single time series and in time series from homogeneous and heterogeneous databases using an Orthogonal Greedy Algorithm (OGA) for saturated linear regression models.The programs implement the…
View article: Educación en Sexualidad, Afectividad y Género. Percepción de estudiantes secundarios en un establecimiento educacional de la comuna de Coronel
Educación en Sexualidad, Afectividad y Género. Percepción de estudiantes secundarios en un establecimiento educacional de la comuna de Coronel Open
Este trabajo presenta algunos hallazgos emergentes dentro de una investigación que se propuso analizar la relación entre afectividad y sexualidad en el programa de educación en Sexualidad, Afectividad y Género, ejecutado en un liceo de la …
View article: A testing approach to clustering scalar time series
A testing approach to clustering scalar time series Open
This article considers clustering stationary scalar time series using their marginal properties and a hierarchical method. Two major issues involved are to detect the existence of clusters and to determine their number. We propose a new te…
View article: Modelling multiple seasonalities with ARIMA: Forecasting Madrid NO2 hourly pollution levels
Modelling multiple seasonalities with ARIMA: Forecasting Madrid NO2 hourly pollution levels Open
Multiple seasonalities often appear in high-frequency data. In this context multiple seasonal components are usually modelled in a deterministic way by trigonometric functions or dummy variables. This assumption may be too strict. Instead,…
View article: A Review of Outlier Detection and Robust Estimation Methods for High Dimensional Time Series Data
A Review of Outlier Detection and Robust Estimation Methods for High Dimensional Time Series Data Open
Diagnostic procedures for finding outliers in high dimensional multivariate time series and robust estimation methods for these data are reviewed. First, methods for searching for outliers assuming that the data have been generated by a Dy…
View article: Effect of TiO2 Nanoparticles and Extrusion Process on the Physicochemical Properties of Biodegradable and Active Cassava Starch Nanocomposites
Effect of TiO2 Nanoparticles and Extrusion Process on the Physicochemical Properties of Biodegradable and Active Cassava Starch Nanocomposites Open
Biodegradable polymers have been strongly recognized as an alternative to replace traditional petrochemical plastics, which have become a global problem due to their long persistence in the environment. In this work, the effect of the addi…
View article: What drives industrial energy prices?
What drives industrial energy prices? Open
View article: Understanding complex predictive models with ghost variables
Understanding complex predictive models with ghost variables Open
View article: A Conversation with Dennis Cook
A Conversation with Dennis Cook Open
Dennis Cook is a Full Professor, School of Statistics, at the University of Minnesota. He received his BS degree in Mathematics from Northern Montana College, and MS and PhD degrees in Statistics from Kansas State University. He has served…
View article: Index
Index Open
matrix,
View article: On a new procedure for identifying a dynamic common factor model
On a new procedure for identifying a dynamic common factor model Open
In the context of the exact dynamic common factor model, canonical correlations in a multivariate time series are used to identify the number of latent common factors. In this paper, we establish a relationship between canonical correlatio…
View article: Some recent methods for analyzing high dimensional time series
Some recent methods for analyzing high dimensional time series Open
This article analyzes six recent advances in the analyses of high dimensional time series.The first two procedures have the objective of understanding the structure of the set of series: dynamic quantiles for data visualization and cluster…
View article: DETERMINACIÓN DE MORINA EN TÉ VERDE Y CAFÉ POR VOLTAMPEROMETRÍA DE ADSORCIÓN UTILIZANDO ELECTRODOS DE CARBONO MODIFICADOS CON POLI (3,4-ETILENDIOXITIOFENO) Y LÍQUIDO IÓNICO
DETERMINACIÓN DE MORINA EN TÉ VERDE Y CAFÉ POR VOLTAMPEROMETRÍA DE ADSORCIÓN UTILIZANDO ELECTRODOS DE CARBONO MODIFICADOS CON POLI (3,4-ETILENDIOXITIOFENO) Y LÍQUIDO IÓNICO Open
Este artículo presenta un método sensible y selectivo para la determinación de morina (MR) en presencia de rutina (RT) y quercetina (QC) en un electrodo de carbono serigrafiado (SPCE) recubierto con poli (3,4-etilendioxitiofeno) (PEDOT) y …
View article: A robust procedure to build dynamic factor models with cluster structure
A robust procedure to build dynamic factor models with cluster structure Open
View article: <b>gdpc</b>: An <i>R</i> Package for Generalized Dynamic Principal Components
<b>gdpc</b>: An <i>R</i> Package for Generalized Dynamic Principal Components Open
gdpc is an R package for the computation of the generalized dynamic principal components proposed in Peña and Yohai (2016). In this paper, we briefly introduce the problem of dynamical principal components, propose a solution based on a re…
View article: Understanding complex predictive models with Ghost Variables
Understanding complex predictive models with Ghost Variables Open
We propose a procedure for assigning a relevance measure to each explanatory variable in a complex predictive model. We assume that we have a training set to fit the model and a test set to check the out of sample performance. First, the i…
View article: Empirical Dynamic Quantiles for Visualization of High-Dimensional Time Series
Empirical Dynamic Quantiles for Visualization of High-Dimensional Time Series Open
The empirical quantiles of independent data provide a good summary of the underlying distribution of the observations. For high-dimensional time series defined in two dimensions, such as in space and time, one can define empirical quant…
View article: Forecasting Multiple Time Series With One-Sided Dynamic Principal Components
Forecasting Multiple Time Series With One-Sided Dynamic Principal Components Open
We define one-sided dynamic principal components (ODPC) for time series as linear combinations of the present and past values of the series that minimize the reconstruction mean squared error. Usually dynamic principal components have been…
View article: Clustering time series by linear dependency
Clustering time series by linear dependency Open
View article: 2018 American Control Conference Wisconsin Center / Hilton Milwaukee City Center Milwaukee, WI, USA
2018 American Control Conference Wisconsin Center / Hilton Milwaukee City Center Milwaukee, WI, USA Open
View article: Forecasting Multiple Time Series with One-Sided Dynamic Principal\n Components
Forecasting Multiple Time Series with One-Sided Dynamic Principal\n Components Open
We define one-sided dynamic principal components (ODPC) for time series as\nlinear combinations of the present and past values of the series that minimize\nthe reconstruction mean squared error. Previous definitions of dynamic\nprincipal c…
View article: Clustering Big Data by Extreme Kurtosis Projections
Clustering Big Data by Extreme Kurtosis Projections Open
Clustering Big Data is an important problem because large samples of many variables are usually heterogeneous and include mixtures of several populations. It often happens that only some of a large set of variables are useful for clusterin…
View article: Generalized Dynamic Principal Components
Generalized Dynamic Principal Components Open
Brillinger defined dynamic principal components (DPC) for time series based on a reconstruction criterion. He gave a very elegant theoretical solution and proposed an estimator which is consistent under stationarity. Here, we propose a new…
View article: Design of Aero Engine Structures Using Additive Manufacturing
Design of Aero Engine Structures Using Additive Manufacturing Open