(2016). Modeling Discrete Time-to-Event Data. Springer, Dordecht.Tutz, Gerhard, and Matthias Schmid. 2016. Modeling Discrete Time-to-Event Data. New York: Springer. doi:10.1007/978-3-319-28158-2.Tutz, G. and Schmid, M. (2016) Modeling Discrete Time-to-Event Data. Springer Series in...
作者:Sarjoughian, Hessam S.; Sarjoughian, Hessam S.; Cellier, Francois E. 出版年:2001-6 页数:428 定价:$ 123.17 ISBN:9780387950655 豆瓣评分 目前无人评价 评价: 推荐 内容简介· ··· During the 1990s the computing industry has witnessed many advances in mobile and enterprise computing. Many...
In an industrial IoT scenario, live telemetry data produced by devices, sensors, or tags can be continuous or discrete. We’re excited to share thatAzure Time Series Insightscan now process discrete values, enabling users to view up to 100 states. With thisnew feature,...
Discrete Event Modeling and Simulation Technologies 作者:Hessam S·Sarjoughian/Francois E·Cellier 页数:397 ISBN:9781441928689 豆瓣评分 目前无人评价 写笔记 写书评 加入购书单 分享到
Using discrete-event simulation modeling, the movement of a train from point A to point B is modeled with two events, namely a departure and an arrival. The actual movement of the train would be modeled as a time delay between the departure and arrival events. These events and movement betw...
Cox Regression builds a predictive model for time-to-event data. The model produces a survival function that predicts the probability that the event of interest has occurred at a given timetfor given values of the predictor variables. The shape of the survival function and the regression coeffici...
Time to event data: Time to the recovery of diseases in hours. PR and BT from baseline up to hospital discharge of 214 sample pneumonia patients were measured corre- spondingly and approximately every six hours of the day and considered a maximum of 17 follow ups for each of the two ...
SimEvents® provides a discrete-event simulation engine and component library for analyzing event-driven system models and optimizing performance characteristics such as latency, throughput, and packet loss. With SimEvents, you can study the effects of task timing and resource usage on the performance...
This information is used as a conversion factor to relate the SPR signal for a given experiment to an average quantity of antibodies bound per structure. The second aspect of the pipeline is the fitting of a continuous-time Markov chain model to the SPR binding data of both one-antigen and...
A: Data modeling goes through eight discrete steps: identifying data entity types; identifying the attributes associated with them; applying naming conventions; identifying the relationships between data types; applying patterns (or templates) to make sure best-practice models are used; assigning keys ...