Results 31 to 40 of about 62,954 (311)

Autoregressive Diffusion Models

, 2021
We introduce Autoregressive Diffusion Models (ARDMs), a model class encompassing and generalizing order-agnostic autoregressive models (Uria et al., 2014) and absorbing discrete diffusion (Austin et al., 2021), which we show are special cases of ARDMs under mild assumptions. ARDMs are simple to implement and easy to train. Unlike standard ARMs, they do
Hoogeboom, Emiel, Gritsenko, Alexey A., Bastings, Jasmijn, Poole, Ben, Berg, Rianne van den, Salimans, Tim   +5 more
openaire   +2 more sources

Profit rates in the developed capitalist economies: a time series investigation [PDF]

PSL Quarterly Review, 2017
This paper examines whether there is empirical evidence to support the hypothesis of a secular decline in the economy-wide profit rates, as predicted by classical economic theories. We specifically consider profit rates in the OECD economies based on the
Ivan D. Trofimov
doaj  

A Unified Test for the AR Error Structure of an Autoregressive Model

Axioms, 2022
A direct application of autoregressive (AR) models with independent and identically distributed (iid) errors is sometimes inadequate to fit the time series data well.
Xinyi Wei, Xiaohui Liu, Yawen Fan, Li Tan, Qing Liu   +4 more
doaj   +1 more source

First-order planar autoregressive model

Modern Stochastics: Theory and Applications
This paper establishes the conditions for the existence of a stationary solution to the first-order autoregressive equation on a plane as well as properties of the stationary solution.
Sergiy Shklyar
doaj   +1 more source

Nonlinearity and Spatial Autocorrelation in Species Distribution Modeling: An Example Based on Weakfish (Cynoscion regalis) in the Mid-Atlantic Bight

Fishes, 2022
Nonlinearity and spatial autocorrelation are common features observed in marine fish datasets but are often ignored or not considered simultaneously in modeling. Both features are often present within ecological data obtained across extensive spatial and
Yafei Zhang, Yan Jiao, Robert J. Latour
doaj   +1 more source

Heart Rate Modeling and Prediction Using Autoregressive Models and Deep Learning

Sensors, 2021
Physiological time series are affected by many factors, making them highly nonlinear and nonstationary. As a consequence, heart rate time series are often considered difficult to predict and handle.
Alessio Staffini, Thomas Svensson, Ung-il Chung, Akiko Kishi Svensson   +3 more
doaj   +1 more source

​Did a Non‐Medical Biosimilar Switching Policy Cause an Increase in Non‐Biologic/Biosimilar Health Care Resource Utilization or Cost in Patients With Inflammatory Arthritis?

Arthritis Care &Research, EarlyView.
Objective This study aimed to evaluate the impact of a series of policies that mandated switching patients with inflammatory arthritis (IA) from an originator biologic to a biosimilar in British Columbia, Canada, on health care resource use and cost.
HaoHung Dang, Sandra Blitz, Nick Bansback, Michael Law, Mark Harrison   +4 more
wiley   +1 more source

Performance evaluation of photovoltaic scenario generation

Frontiers in Physics
Photovoltaic scenario generation plays a critical role in power systems characterized by high diversity and fluctuation. Despite recent theoretical advancements, effectively evaluating the performance of photovoltaic scenario generation remains a ...
Siyu Ren, Tongxin Yang, Jun Luo, Gang Wu, Gang Wu, Kai Mao, Bowen Liu   +6 more
doaj   +1 more source

The Effect of Nonzero Autocorrelation Coefficients on the Distributions of Durbin-Watson Test Estimator: Three Autoregressive Models [PDF]

Expert Journal of Economics, 2014
This paper investigates the effect of the nonzero autocorrelation coefficients on the sampling distributions of the Durbin-Watson test estimator in three time-series models that have different variance-covariance matrix assumption, separately.
Mei-Yu LEE
doaj  

Hopfield Neural Networks for Online Constrained Parameter Estimation With Time‐Varying Dynamics and Disturbances

International Journal of Adaptive Control and Signal Processing, EarlyView.
This paper proposes two projector‐based Hopfield neural network (HNN) estimators for online, constrained parameter estimation under time‐varying data, additive disturbances, and slowly drifting physical parameters. The first is a constraint‐aware HNN that enforces linear equalities and inequalities (via slack neurons) and continuously tracks the ...
Miguel Pedro Silva
wiley   +1 more source