在非线性生长模型中的贝叶斯推断和在黑乌特雷拉纳中测试性二形态的假设测试
Rafaela de Carvalho Salvador1, Adriele Aparecida Pereira2, Tales Jesus Fernandes1
1Department of Statistics, Federal University of Lavras (UFLA), Lavras, MG, Brazil.
Poultry science
|October 16, 2025
概括
这项研究应用贝叶斯方法来建模黑乌特拉纳的生长,发现·伯塔兰菲模型最适合. 性二态性仅在非对称体重中观察到,男性表现出更高的值.
科学领域:
- 动物科学动物科学
- 定量生物学 定量生物学
- 统计建模 统计建模
背景情况:
- 禽类的生长是复杂的,受到诸如性变态等因素的影响.
- 非线性模型是描述动物生长曲线的标准.
- 贝叶斯推理在增长研究中提供了强大的参数估计和不确定性量化.
研究的目的:
- 选择最佳的非线性模型 (Logistic,Gompertz,Brody,von Bertalanffy) 用于黑乌特雷拉纳的生长.
- 在家禽生长中应用贝叶斯学方法进行参数估计和模型比较.
- 用贝叶斯假设测试来研究生长参数中的性二态.
主要方法:
- 将非线性生长模型 (Logistic,Gompertz,Brody,von Bertalanffy) 与体重数据相适应.
- 使用贝叶斯推理与"brms"R包和哈密尔顿的蒙特卡洛 (NUTS采样器).
- 采用Savage-Dickey方法来测试贝叶斯假设的性二态.
主要成果:
- ·伯塔兰菲 (von Bertalanffy) 和戈默茨 (Gompertz) 的模型最好地描述了的生长,而不论性别.
- 贝叶斯分析揭示了在非对称体重中显著的性二态.
- 雄性黑乌特雷拉纳的非对称体重明显高于雌性.
结论:
- 贝叶斯式方法对于模拟家禽生长动态是有效的.
- 黑乌特雷拉纳的两性二态性主要表现在不对称体重上.
- 这项研究为分析家禽生长和性变态提供了强大的框架.
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