Time-varying priority queuing models for human dynamics

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Modeling and Forecasting Iranian Inflation with Time Varying BVAR Models

This paper investigates the forecasting performance of different time-varying BVAR models for Iranian inflation. Forecast accuracy of a BVAR model with Litterman’s prior compared with a time-varying BVAR model (a version introduced by Doan et al., 1984); and a modified time-varying BVAR model, where the autoregressive coefficients are held constant and only the deterministic components are allo...

متن کامل

MODELLING AND ANALYSIS OF A DISCRETE-TIME PRIORITY QUEUING COMPUTER NETWORK WITH PRIORITY JUMPS USING PROBABILITY GENERATING FUNCTIONS

Priority queues have a great importance in the study of computer communication networks in which different types of traffic require different quality of service standards. The discrete-time non-preemptive priority queuing model with priority jumps is proposed in this paper. On the basis of probability generating functions mean system contents and mean queuing delay characteristics are obtained....

متن کامل

Changing dynamics: Time-varying autoregressive models using generalized additive modeling.

In psychology, the use of intensive longitudinal data has steeply increased during the past decade. As a result, studying temporal dependencies in such data with autoregressive modeling is becoming common practice. However, standard autoregressive models are often suboptimal as they assume that parameters are time-invariant. This is problematic if changing dynamics (e.g., changes in the tempora...

متن کامل

Time-Varying Gaussian Graphical Models of Molecular Dynamics Data

We introduce an algorithm for learning sparse, time-varying undirected probabilistic graphical models of Molecular Dynamics (MD) data. Our method computes a maximum a posteriori (MAP) estimate of the topology and parameters of the model (i.e., structure learning) using L1regularization of the negative log-likelihood (aka ‘Graphical Lasso’) to ensure sparsity, and a kernel to ensure smoothly var...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Physical Review E

سال: 2012

ISSN: 1539-3755,1550-2376

DOI: 10.1103/physreve.85.066101