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05/31/2023
Forecasting high-dimensional functional time series: Application to sub-national age-specific mortality
We consider modeling and forecasting high-dimensional functional time se...
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05/25/2023
Forecasting intraday financial time series with sieve bootstrapping and dynamic updating
Intraday financial data often take the form of a collection of curves th...
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04/14/2023
Detection and Estimation of Structural Breaks in High-Dimensional Functional Time Series
In this paper, we consider detecting and estimating breaks in heterogene...
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04/04/2023
A nonlinearity and model specification test for functional time series
An important issue in functional time series analysis is whether an obse...
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12/08/2022
Fractionally integrated curve time series with cointegration
We introduce methods and theory for fractionally cointegrated curve time...
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04/05/2022
A robust scalar-on-function logistic regression for classification
Scalar-on-function logistic regression, where the response is a binary o...
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03/09/2022
A Robust Functional Partial Least Squares for Scalar-on-Multiple-Function Regression
The scalar-on-function regression model has become a popular analysis to...
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03/09/2022
Factor-augmented model for functional data
We propose modeling raw functional data as a mixture of a smooth functio...
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01/04/2022
Clustering and Forecasting Multiple Functional Time Series
Modelling and forecasting homogeneous age-specific mortality rates of mu...
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12/16/2021
A model sufficiency test using permutation entropy
Using the ordinal pattern concept in permutation entropy, we propose a m...
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12/01/2021
AR-sieve Bootstrap for High-dimensional Time Series
This paper proposes a new AR-sieve bootstrap approach on high-dimensiona...
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11/09/2021
Function-on-function linear quantile regression
In this study, we propose a function-on-function linear quantile regress...
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11/08/2021
Is the group structure important in grouped functional time series?
We study the importance of group structure in grouped functional time se...
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11/01/2021
A robust partial least squares approach for function-on-function regression
The function-on-function linear regression model in which the response a...
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09/13/2021
Function-on-function partial quantile regression
In this paper, a functional partial quantile regression approach, a quan...
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09/09/2021
Multi-population mortality forecasting using high-dimensional functional factor models
This paper proposes a two-fold factor model for high-dimensional functio...
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07/22/2021
Dynamic functional time-series forecasts of foreign exchange implied volatility surfaces
This paper presents static and dynamic versions of univariate, multivari...
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06/02/2021
Feature Extraction for Functional Time Series: Theory and Application to NIR Spectroscopy Data
We propose a novel method to extract global and local features of functi...
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04/26/2021
A functional autoregressive model based on exogenous hydrometeorological variables for river flow prediction
In this research, a functional time series model was introduced to predi...
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02/04/2021
Factor-augmented Smoothing Model for Functional Data
We propose modeling raw functional data as a mixture of a smooth functio...
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02/01/2021
Double bootstrapping for visualising the distribution of descriptive statistics of functional data
We propose a double bootstrap procedure for reducing coverage error in t...
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12/19/2020
Functional time series forecasting of extreme values
We consider forecasting functional time series of extreme values within ...
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12/09/2020
A partial least squares approach for function-on-function interaction regression
A partial least squares regression is proposed for estimating the functi...
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11/16/2020
Change point detection for COVID-19 excess deaths in Belgium
Emerging at the end of 2019, COVID-19 has become a public health threat ...
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11/16/2020
Robust bootstrap prediction intervals for univariate and multivariate autoregressive time series models
The bootstrap procedure has emerged as a general framework to construct ...
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11/09/2020
Bayesian bandwidth estimation for local linear fitting in nonparametric regression models
This paper presents a Bayesian sampling approach to bandwidth estimation...
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10/11/2020
Granger causality of bivariate stationary curve time series
We study causality between bivariate curve time series using the Granger...
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08/19/2020
Synergy in fertility forecasting: Improving forecast accuracy through model averaging
Accuracy in fertility forecasting has proved challenging and warrants re...
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07/07/2020
Forecasting Australian subnational age-specific mortality rates
When modeling sub-national mortality rates, it is important to incorpora...
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06/25/2020
Retiree mortality forecasting: A partial age-range or a full age-range model?
An essential input of annuity pricing is the future retiree mortality. F...
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04/08/2020
Bootstrap Prediction Bands for Functional Time Series
A bootstrap procedure for constructing pointwise or simultaneous predict...
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03/17/2020
A comparison of Hurst exponent estimators in long-range dependent curve time series
The Hurst exponent is the simplest numerical summary of self-similar lon...
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03/12/2020
A comparison of parameter estimation in function-on-function regression
Recent technological developments have enabled us to collect complex and...
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02/24/2020
Bayesian bandwidth estimation and semi-metric selection for a functional partial linear model with unknown error density
This study examines the optimal selections of bandwidth and semi-metric ...
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01/10/2020
Forecasting multiple functional time series in a group structure: an application to mortality
When modeling sub-national mortality rates, we should consider three fea...
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01/08/2020
Functional linear models for interval-valued data
Aggregation of large databases in a specific format is a frequently used...
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12/15/2019
On function-on-function regression: Partial least squares approach
Functional data analysis tools, such as function-on-function regression ...
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09/21/2019
Implied volatility surface predictability: the case of commodity markets
Recent literature seek to forecast implied volatility derived from equit...
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09/01/2019
Dynamic principal component regression for forecasting functional time series in a group structure
When generating social policies and pricing annuity at national and subn...
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08/05/2019
Forecasting age distribution of death counts: An application to annuity pricing
We consider a compositional data analysis approach to forecasting the ag...
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08/01/2019
Forecasting functional time series using weighted likelihood methodology
Functional time series whose sample elements are recorded sequentially o...
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05/10/2019
Dynamic principal component regression: Application to age-specific mortality forecasting
In areas of application, including actuarial science and demography, it ...
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01/17/2019
A robust functional time series forecasting method
Univariate time series often take the form of a collection of curves obs...
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01/08/2019
Uncovering predictability in the evolution of the WTI oil futures curve
Accurately forecasting the price of oil, the world's most actively trade...
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11/30/2018
Intraday forecasts of a volatility index: Functional time series methods with dynamic updating
As a forward-looking measure of future equity market volatility, the VIX...
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10/19/2018
Estimation of a functional single index model with dependent errors and unknown error density
The problem of error density estimation for a functional single index mo...
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10/03/2018
Semiparametric Regression using Variational Approximations
Semiparametric regression offers a flexible framework for modeling non-l...
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10/02/2018
High-dimensional functional time series forecasting: An application to age-specific mortality rates
We address the problem of forecasting high-dimensional functional time s...
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09/28/2018