PINE LIBRARY
已更新 ArrayStatistics

Library "ArrayStatistics"
Statistic Functions using arrays.
rms(sample) Root Mean Squared
Parameters:
Returns: float
skewness_pearson1(sample) Pearson's 1st Coefficient of Skewness.
Parameters:
Returns: float
skewness_pearson2(sample) Pearson's 2nd Coefficient of Skewness.
Parameters:
Returns: float
pearsonr(sample_a, sample_b) Pearson correlation coefficient measures the linear relationship between two datasets.
Parameters:
Returns: float p
kurtosis(sample) Kurtosis of distribution.
Parameters:
Returns: float
range_int(sample, percent) Get range around median containing specified percentage of values.
Parameters:
Returns: tuple with [int, int], Returns the range which containes specifies percentage of values.
Statistic Functions using arrays.
rms(sample) Root Mean Squared
Parameters:
- sample: float array, data sample points.
Returns: float
skewness_pearson1(sample) Pearson's 1st Coefficient of Skewness.
Parameters:
- sample: float array, data sample.
Returns: float
skewness_pearson2(sample) Pearson's 2nd Coefficient of Skewness.
Parameters:
- sample: float array, data sample.
Returns: float
pearsonr(sample_a, sample_b) Pearson correlation coefficient measures the linear relationship between two datasets.
Parameters:
- sample_a: float array, sample with data.
- sample_b: float array, sample with data.
Returns: float p
kurtosis(sample) Kurtosis of distribution.
Parameters:
- sample: float array, data sample.
Returns: float
range_int(sample, percent) Get range around median containing specified percentage of values.
Parameters:
- sample: int array, Histogram array.
- percent: float, Values percentage around median.
Returns: tuple with [int, int], Returns the range which containes specifies percentage of values.
發行說明
added new function:average_weighted(sample, weights) Computes a weighted average (the mean, where each value is weighted by its relative importance).
Parameters:
sample: float array, data sample.
weights: float array, weights to apply to samples.
Returns: float
發行說明
v3Updated: display examples on chart.
Added:
arithmetic_geometric_mean_simple(value_a, value_b, tolerance_value) Calculate the arithmetic-geometric mean of two numbers (_value_a, _value_b).
Parameters:
value_a: float, number value.
value_b: float, number value.
tolerance_value: float, number value, default=1e-12.
Returns: float
arithmetic_geometric_mean(sample, tolerance_value) Computes the arithmetic geometric mean of a sequence of values.
Parameters:
sample: float array, data sample.
tolerance_value: float, number value, default=1e-12.
Returns: float
發行說明
v4Added:
zscore_simple(value, mean, deviation) Computes the simple version of the z-score formula.
Parameters:
value: float, data value.
mean: float, data mean.
deviation: float, the standard deviation of the data.
Returns: float.
zscore(sample) Computes the z-score of a data sample values.
Parameters:
sample: float array, data values.
Returns: float array.
發行說明
v5Updated:
arithmetic_geometric_mean() was not computed correctly, thank you, InvestCHK for pointing it out.
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Pine腳本庫
秉持 TradingView 一貫的共享精神,作者將此 Pine 程式碼發佈為開源庫,讓社群中的其他 Pine 程式設計師能夠重複使用。向作者致敬!您可以在私人專案或其他開源發佈中使用此庫,但在公開發佈中重複使用該程式碼需遵守社群規範。
免責聲明
這些資訊和出版物並不意味著也不構成TradingView提供或認可的金融、投資、交易或其他類型的意見或建議。請在使用條款閱讀更多資訊。