v0.1.0

v0.1.0 — initial release

First release of dsh-probstat: deterministic probability & statistical-inference math for DeepSeek Harness, zero runtime dependencies.

Four tools:

• dist_calc — pdf / cdf / survival / quantile / stats for six distributions: normal, binomial, poisson, exponential, uniform, geometric
• z_score — standard-normal table math: z ↔ probability/percentile, two-sided p-values, interval probabilities
• confidence_interval — mean intervals (known σ → z; unknown σ → Student-t, df = n−1) and proportion intervals (Wilson score method)
• event_probability — union / intersection / conditional / Bayes / complement / at-least-one identities

Numerics: normal cdf via A&S 7.1.26 erf fit (|err| ≤ 1.5e-7), quantile via Acklam inverse normal (rel. err < 1.15e-9); binomial/poisson exact recurrence summation; Student-t via Lentz continued fraction + Lanczos log-gamma, cross-checked against published t-table values. 37 tests, anchors generated by an independent Python oracle (test/anchors-probstat.py) and cross-validated with published z/t-table values.

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v0.1.0 — 首发版本

dsh-probstat 首发：DeepSeek Harness 概率与统计推断数学工具箱，零运行时依赖。

四个工具：

• dist_calc — 六种分布（正态/二项/泊松/指数/均匀/几何）的 pdf / cdf / 生存函数 / 分位数 / 统计量
• z_score — 标准正态表换算：z ↔ 概率/百分位、双侧 p 值、区间概率
• confidence_interval — 均值置信区间（σ 已知走 z；未知走 t，df = n−1）+ 比例 Wilson 区间
• event_probability — 并 / 交 / 条件 / 贝叶斯 / 补集 / 至少一次成功恒等式

数值方法：正态 CDF 用 A&S 7.1.26 erf 拟合（绝对误差 ≤ 1.5e-7），分位数用 Acklam 逆正态（相对误差 < 1.15e-9）；二项/泊松递推精确求和；t 分布用连分式不完全贝塔 + Lanczos log-Gamma，并与公开 t 表值交叉验证。37 项测试，锚点由独立 Python oracle（test/anchors-probstat.py）生成。

Install: dsh plugin --profile web add github:TYEclipse/dsh-probstat