nuget
高斯条件概率分布参数 Xi | Pa(Xi) ~ N(β0 + β1·Pa1 + β2·Pa2 + ... + βk·Pak, σ²)
BnCPD
01 Syntax
SMRUCC.genomics.Analysis.BNLearn.Core.BnCPD
02 Methods
| Name | Overloads | Summary |
|---|---|---|
| ConditionalMean | 1 | 根据父节点值计算条件均值 E[Xi | Pa(Xi)] = β0 + Σ βj·Pa_j |
| Sample | 1 | 从条件分布中采样 Xi ~ N(β0 + Σ βj·Pa_j, σ²) |
| LogDensity | 1 | 计算条件概率密度 f(Xi | Pa(Xi)) = (1/√(2πσ²))·exp(-(Xi-μ)²/(2σ²)) |
| Clone | 1 | |
| ToString | 1 |
03 Properties
| Name | Overloads | Summary |
|---|---|---|
| NodeIndex | 1 | 所属节点索引 |
| Intercept | 1 | 截距 β0 |
| Coeffs | 1 | 回归系数 βj，对应每个父节点 |
| ParentIndices | 1 | 父节点索引列表（与 Coeffs 一一对应） |
| ResidualSD | 1 | 残差标准差 σ |
| ResidualVariance | 1 | 残差方差 σ² |
| RSquared | 1 | 拟合 R² |
| BIC | 1 | BIC 评分 |
| NSamples | 1 | 样本数 |
04 Members
ConditionalMean(
Double())根据父节点值计算条件均值 E[Xi | Pa(Xi)] = β0 + Σ βj·Pa_j
Sample(
Double())从条件分布中采样 Xi ~ N(β0 + Σ βj·Pa_j, σ²)
LogDensity(
Double, Double())计算条件概率密度 f(Xi | Pa(Xi)) = (1/√(2πσ²))·exp(-(Xi-μ)²/(2σ²))
NodeIndex
所属节点索引
Intercept
截距 β0
Coeffs
回归系数 βj，对应每个父节点
Remarks
Coeffs(j) 对应 Parents(j) 的回归系数
ParentIndices
父节点索引列表（与 Coeffs 一一对应）
ResidualSD
残差标准差 σ
ResidualVariance
残差方差 σ²
RSquared
拟合 R²
BIC
BIC 评分
NSamples
样本数
Clone()
ToString()