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Modelling mobility trends - update including 2023 ODiN data
Discussion paper about a method based on time-series multilevel modelling to estimate detailed mobility trends corrected for discontinuities due to survey redesigns.
Mode-specific measurement biases and selection biases in health statistics
Mixed-mode adaptive survey designs have become a standard in many survey settings. Also the combination of mixing modes and adapting effort has been elaborated and applied. However, the focus has...
COVID-19 hospitalizations: fostering decision-making in future pandemics
Effective and targeted decision-making during pandemics requires accurate forecasting of key health outcomes such as hospitalizations. This study investigates the relationship between the weekly...
NNPF: Neural Network Particle Filter for Time Series Data
Discussion paper on a novel particle filter based on a neural network for time series analysis.
Elastic energy of networks
The paper is about invariants of networks by labeling and relabeling its nodes or arcs. These invariants can be used to classify networks as to their complexity, or to distinguish non-isomorphic...
Redistribution of mass and probabilities
Models to transport goods or matter can also be used to disaggregate probability measures defined on 2D-tables.
Impact redesign on monthly labour force figures
Estimating monthly figures on the Dutch labour force during the transition to a new survey design.
Including migration in hedonic valuation: earthquakes
This paper is an attempt to estimate the willingness to pay for earthquake reduction in and around the province of Groningen (2012-2018), whilst using a discrete choice model to incorporate...
An estimator for ratios of Poisson distributed quantities
A common task for national statistical institutes is to estimate the size of a subpopulation, with certain specific characteristics, as a proportion of a larger population or subpopulation. This...
Quarterly figures on Dutch health by time series models
Estimation of quarterly figures on Dutch health during the Covid-19 pandemic by structural time series models.
Estimating consumer confidence using time series models
Discussion paper about estimating monthly consumer confidence figures
Time series modelling of mobility trends, 1999-2020
Discussion paper about a method to estimate detailed mobility trends corrected for discontinuities due to redesigns
Multivariate density estimation by neural networks
Discussion paper about a nonparametric method to estimate the probability density of data sources
Potential Biases in Network Reconstruction Methods
Potential Biases in Network Reconstruction Methods Not Maximizing Entropy
Monthly Labour Force Figures during COVID-19
Discussion paper about estimating monthly labour force figures during the COVID-19 pandemic in the Netherlands
Time varying correlations in state space models
Discussion paper about a method to estimate time varying state correlations in multivariate state space models
Time series modeling of mobility trends – update 2020
Discussion paper about a method to estimate detailed mobility trends corrected for discontinuities due to redesigns
Geographic location estimation of mobile devices
A working paper in which a modular Bayesian framework is proposed to estimate the geographic location of mobile devices from mobile phone network data.
Nowcasting GDP growth rate: a potential substitute for the current flash estimate
Currently Statistics Netherlands provides a first estimate of the GDP growth rate 45 days after the end of the reference quarter.
A dynamic factor model for unemployment statistics
Discussiepaper over een methode om een groot aantal hulpreeksen afkomstig uit big data bronnen te gebruiken bij het schatten van de maandelijkse werkloze beroepsbevolking.