相关实验视频

Updated: Jun 24, 2026

Windowing Chicken Eggs for Developmental Studies
15:01

Windowing Chicken Eggs for Developmental Studies

Published on: October 1, 2007

27.8K

模拟和预测使用时间序列方法在肉中死亡到达:泰国的案例研究

Chalita Jainonthee1,2,3, Panneepa Sivapirunthep4, Pranee Pirompud5

  • 1Faculty of Veterinary Medicine, Chiang Mai University, Chiang Mai 50100, Thailand.

Animals : an open access journal from MDPI
|April 26, 2025
PubMed
概括

无抗生素的肉生产面临运输死亡率的挑战. 像TBATS和ETS这样的时间序列模型准确预测到达时死亡的百分比,有助于主动管理和改善动物福利.

关键词:
排放交易系统 (ETS) 是一个.这就是NNAR NNAR.萨里玛萨里玛是什么意思在TBATS中,TBATS是TBATS.在XGBoost中使用.没有抗生素的肉生产.在抵达时死亡.禽类的福利 禽类的福利季节性模式的季节性模式时间序列预测时间序列预测

更多相关视频

Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients07:34

Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients

Published on: August 22, 2018

8.2K
In Ovo Feeding of Commercial Broiler Eggs: An Accurate and Reproducible Method to Affect Muscle Development and Growth06:38

In Ovo Feeding of Commercial Broiler Eggs: An Accurate and Reproducible Method to Affect Muscle Development and Growth

Published on: September 20, 2021

2.3K

相关概念视频

Introduction To Survival Analysis01:18

Introduction To Survival Analysis

Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
The primary goal of survival analysis is to estimate survival time—the time until a...
Life Tables01:22

Life Tables

A life table is a statistical tool that summarizes the mortality and survival patterns of a population, providing detailed insights into the likelihood of survival or death across different age intervals within a cohort. By organizing data on survival probabilities and mortality rates, life tables offer a clear snapshot of population dynamics over time. They are extensively used in demography, public health, actuarial science, and ecology to analyze life expectancy, design health interventions,...
Assumptions of Survival Analysis01:15

Assumptions of Survival Analysis

Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
Truncation in Survival Analysis01:09

Truncation in Survival Analysis

Truncation in survival analysis refers to the exclusion of individuals or events from the dataset based on specific criteria related to the time of the event. This exclusion can happen in two primary forms: left truncation and right truncation.
Left truncation occurs when individuals who experienced the event of interest before a certain time are not included in the study. This is often due to a "delayed entry" into the study where only those who survive until a certain entry point are observed.
Censoring Survival Data01:09

Censoring Survival Data

Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different reasons...
Survival Tree01:19

Survival Tree

Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a survival tree begins...