Rob J Hyndman
Biographic Data
| ID | 6044862 |
|---|---|
| NAME | Rob J Hyndman |
| GIVEN NAMES | Rob J |
| FAMILY NAME | Hyndman |
| SIGNATURE | HYNDMAN R J |
| AFFILIATIONS | Monash University |
| ORCID | 0000-0002-2140-5352 |
| VERIFIED | Yes |
| TOTAL WORKS | 10 |
| TOTAL CITATIONS | 81 |
| AUTHOR COUNT | 10 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2004 |
| LATEST PUBLICATION YEAR | 2021 |
| H-INDEX | 4 |
Reconstructing Missing and Anomalous Data Collected from High-Frequency In-Situ Sensors in Fresh Waters
In situ sensors that collect high-frequency data are used increasingly to monitor aquatic environments. These sensors are prone to technical errors, resulting in unrecorded observations and/or anomalous values that are subsequently removed and create gaps in time series data. We present a framework based on generalized additive and auto-regressive models to recover these missing data. To mimic sporadically missing (i) single observations and (ii)…
Coherent Mortality Forecasting: The Product-Ratio Method With Functional Time Series Models
When independence is assumed, forecasts of mortality for subpopulations are almost always divergent in the long term. We propose a method for coherent forecasting of mortality rates for two or more subpopulations, based on functional principal components models of simple and interpretable functions of rates. The product-ratio functional forecasting method models and forecasts the geometric mean of subpopulation rates and the ratio of subpopulatio…
The tourism forecasting competition
Point and interval forecasts of mortality rates and life expectancy: A comparison of ten principal component methods
Using the age- and sex-specific data of 14 developed countries, we compare the point and interval forecast accuracy and bias of ten principal component methods for forecasting mortality rates and life expectancy. The ten methods are variants and extens
Detecting trend and seasonal changes in satellite image time series
Automatic Time Series Forecasting: The forecast Package for R
Automatic forecasts of large numbers of univariate time series are often needed in business and other contexts. We describe two automatic forecasting algorithms that have been implemented in the forecast package for R. The first is based on innovations state space models that underly exponential smoothing methods. The second is a step-wise algorithm for forecasting with ARIMA models. The algorithms are applicable to both seasonal and non-seasonal…
Modelling and forecasting Australian domestic tourism
Another look at measures of forecast accuracy
Lee-Carter mortality forecasting: A Multi-Country Comparison of Variants and Extensions
We compare the short- to medium-term accuracy of five variants or extensions of the Lee-Carter method for mortality forecasting. These include the original Lee-Carter, the Lee-Miller and Booth-Maindonald-Smith variants, and the more flexible Hyndman-Ul
Spline interpolation for demographic variables: The monotonicity problem
Modelling and forecasting Australian domestic tourism
Coherent Mortality Forecasting: The Product-Ratio Method With Functional Time Series Models
When independence is assumed, forecasts of mortality for subpopulations are almost always divergent in the long term. We propose a method for coherent forecasting of mortality rates for two or more subpopulations, based on functional principal components models of simple and interpretable functions of rates. The product-ratio functional forecasting method models and forecasts the geometric mean of subpopulation rates and the ratio of subpopulatio…
Lee-Carter mortality forecasting: A Multi-Country Comparison of Variants and Extensions
We compare the short- to medium-term accuracy of five variants or extensions of the Lee-Carter method for mortality forecasting. These include the original Lee-Carter, the Lee-Miller and Booth-Maindonald-Smith variants, and the more flexible Hyndman-Ul
Point and interval forecasts of mortality rates and life expectancy: A comparison of ten principal component methods
Using the age- and sex-specific data of 14 developed countries, we compare the point and interval forecast accuracy and bias of ten principal component methods for forecasting mortality rates and life expectancy. The ten methods are variants and extens
Spline interpolation for demographic variables: The monotonicity problem
Spline interpolation for demographic variables: The monotonicity problem
Another look at measures of forecast accuracy
Lee-Carter mortality forecasting: A Multi-Country Comparison of Variants and Extensions
We compare the short- to medium-term accuracy of five variants or extensions of the Lee-Carter method for mortality forecasting. These include the original Lee-Carter, the Lee-Miller and Booth-Maindonald-Smith variants, and the more flexible Hyndman-Ul
Automatic Time Series Forecasting: The forecast Package for R
Automatic forecasts of large numbers of univariate time series are often needed in business and other contexts. We describe two automatic forecasting algorithms that have been implemented in the forecast package for R. The first is based on innovations state space models that underly exponential smoothing methods. The second is a step-wise algorithm for forecasting with ARIMA models. The algorithms are applicable to both seasonal and non-seasonal…
Modelling and forecasting Australian domestic tourism
Detecting trend and seasonal changes in satellite image time series
The tourism forecasting competition
Point and interval forecasts of mortality rates and life expectancy: A comparison of ten principal component methods
Using the age- and sex-specific data of 14 developed countries, we compare the point and interval forecast accuracy and bias of ten principal component methods for forecasting mortality rates and life expectancy. The ten methods are variants and extens
Coherent Mortality Forecasting: The Product-Ratio Method With Functional Time Series Models
When independence is assumed, forecasts of mortality for subpopulations are almost always divergent in the long term. We propose a method for coherent forecasting of mortality rates for two or more subpopulations, based on functional principal components models of simple and interpretable functions of rates. The product-ratio functional forecasting method models and forecasts the geometric mean of subpopulation rates and the ratio of subpopulatio…
Reconstructing Missing and Anomalous Data Collected from High-Frequency In-Situ Sensors in Fresh Waters
In situ sensors that collect high-frequency data are used increasingly to monitor aquatic environments. These sensors are prone to technical errors, resulting in unrecorded observations and/or anomalous values that are subsequently removed and create gaps in time series data. We present a framework based on generalized additive and auto-regressive models to recover these missing data. To mimic sporadically missing (i) single observations and (ii)…
Mathematics (9 works) · Statistics (9 works) · Econometrics (8 works) · Computer Science (6 works) · Time series (5 works) · Forecasting Techniques and Applications (4 works) · Series (stratigraphy) (4 works) · Biology (3 works) · Data mining (3 works) · Economics (3 works)