Pages that link to "Item:Q5850975"

The following pages link to Predictive Model Assessment for Count Data (Q5850975):

Displaying 44 items.

• Conway–Maxwell–Poisson seasonal autoregressive moving average model (Q3390480) (← links)
• Construction and Visualization of Confidence Sets for Frequentist Distributional Forecasts (Q3391186) (← links)
• Scalable Visualization Methods for Modern Generalized Additive Models (Q3391450) (← links)
• Bayesian nowcasting during the STEC O104:H4 outbreak in Germany, 2011 (Q3465382) (← links)
• Assessing the Impact of a Movement Network on the Spatiotemporal Spread of Infectious Diseases (Q4649048) (← links)
• Modelling multivariate disease rates with a latent structure mixture model (Q4970583) (← links)
• Convolution-closed models for count time series with applications (Q4979107) (← links)
• Integer-valued autoregressive processes with prespecified marginal and innovation distributions: a novel perspective (Q5030977) (← links)
• Bivariate Residual Plots With Simulation Polygons (Q5065985) (← links)
• Test of parameter changes in a class of observation-driven models for count time series (Q5077400) (← links)
• Bivariate models for time series of counts: A comparison study between PBINAR models and dynamic factor models (Q5082661) (← links)
• A Flexible Univariate Autoregressive Time‐Series Model for Dispersed Count Data (Q5111856) (← links)
• Conway–Maxwell–Poisson Autoregressive Moving Average Model for Equidispersed, Underdispersed, and Overdispersed Count Data (Q5135325) (← links)
• Pǿlya–Aeppli regression model for overdispersed count data (Q5142247) (← links)
• Quantification of annual wildfire risk; A spatio-temporal point process approach. (Q5148616) (← links)
• (Q5207225) (← links)
• On count time series prediction (Q5220723) (← links)
• The COM‐Poisson model for count data: a survey of methods and applications (Q5414500) (← links)
• Power law approximations of movement network data for modeling infectious disease spread (Q5420222) (← links)
• An online spatiotemporal prediction model for dengue fever epidemic in <scp>K</scp>aohsiung (<scp>T</scp>aiwan) (Q5420230) (← links)
• A dependent counting INAR model with serially dependent innovation (Q5861472) (← links)
• Copula Regression for Compound Distributions with Endogenous Covariates with Applications in Insurance Deductible Pricing (Q5881112) (← links)
• Case Study in Evaluating Time Series Prediction Models Using the Relative Mean Absolute Error (Q5884456) (← links)
• Uncertainty quantification in complex simulation models using ensemble copula coupling (Q5965044) (← links)
• Zero-modified count time series with Markovian intensities (Q6076568) (← links)
• Predictive Inference Based on Markov Chain Monte Carlo Output (Q6088268) (← links)
• On the aggregation of probability assessments: regularized mixtures of predictive densities for eurozone inflation and real interest rates (Q6090580) (← links)
• Latent Gaussian Count Time Series (Q6107233) (← links)
• Enhanced pricing and management of bundled insurance risks with dependence-aware prediction using pair copula construction (Q6118721) (← links)
• Seasonal count time series (Q6135336) (← links)
• Regression diagnostics meets forecast evaluation: conditional calibration, reliability diagrams, and coefficient of determination (Q6144424) (← links)
• High-dimensional modeling of spatial and spatio-temporal conditional extremes using INLA and Gaussian Markov random fields (Q6144814) (← links)
• Lumpy and intermittent retail demand forecasts with score-driven models (Q6167355) (← links)
• Forecasting overdispersed INAR(1) count time series with negative binomial marginal (Q6172610) (← links)
• Dynamic spatial regression models for space‐varying forest stand tables (Q6179538) (← links)
• Alternative procedures in dependent counting INAR process with application on COVID-19 (Q6181886) (← links)
• A multivariate heavy-tailed integer-valued GARCH process with EM algorithm-based inference (Q6494391) (← links)
• Calibration diagnostics for point process models via the probability integral transform (Q6537847) (← links)
• Count-valued time series models for COVID-19 daily death dynamics (Q6541782) (← links)
• One-misrecorded Poisson INAR(1) model via two random operators with application to crime and economics data (Q6547354) (← links)
• The balanced discrete Burr–Hatke model and mixing INAR(1) process: properties, estimation, forecasting and COVID-19 applications (Q6579805) (← links)
• GAMLSS for Longitudinal Multivariate Claim Count Models (Q6583009) (← links)
• A zero-inflated endemic-epidemic model with an application to measles time series in Germany (Q6595078) (← links)
• The balanced discrete triplet Lindley model and its INAR(1) extension: properties and COVID-19 applications (Q6636248) (← links)