PINE LIBRARY
已更新 stats

Library "stats"
stats
factorial(x)
factorial
Parameters:
x (int)
standardize(x, length, lengthSmooth)
standardize
description Moving Standardization of a time series.
Parameters:
x (float)
length (int)
lengthSmooth (int)
dnorm(x, mean, sd)
dnorm
description Approximation for Normal Density Function.
Parameters:
x (float)
mean (float)
sd (float)
pnorm(x, mean, sd, log)
pnorm
description Approximation for Normal Cumulative Distribution Function.
Parameters:
x (float)
mean (float)
sd (float)
log (bool)
ewma(x, length, tau_hl)
ewma
description Exponentially Weighted Moving Average.
Parameters:
x (float)
length (int)
tau_hl (float)
ewm_sd(x, length, tau_hl)
Exponentially Weighted Moving Standard Deviation.
Parameters:
x (float)
length (int)
tau_hl (float)
ewm_scoring(x, length, tau_hl)
ewm_scoring
description Exponentially Weighted Moving Standardization:
Parameters:
x (float)
length (int)
tau_hl (float)
stats
factorial(x)
factorial
Parameters:
x (int)
standardize(x, length, lengthSmooth)
standardize
description Moving Standardization of a time series.
Parameters:
x (float)
length (int)
lengthSmooth (int)
dnorm(x, mean, sd)
dnorm
description Approximation for Normal Density Function.
Parameters:
x (float)
mean (float)
sd (float)
pnorm(x, mean, sd, log)
pnorm
description Approximation for Normal Cumulative Distribution Function.
Parameters:
x (float)
mean (float)
sd (float)
log (bool)
ewma(x, length, tau_hl)
ewma
description Exponentially Weighted Moving Average.
Parameters:
x (float)
length (int)
tau_hl (float)
ewm_sd(x, length, tau_hl)
Exponentially Weighted Moving Standard Deviation.
Parameters:
x (float)
length (int)
tau_hl (float)
ewm_scoring(x, length, tau_hl)
ewm_scoring
description Exponentially Weighted Moving Standardization:
Parameters:
x (float)
length (int)
tau_hl (float)
發行說明
v2Removed:
ewma(x, length, tau_hl)
ewma
description Exponentially Weighted Moving Average.
ewm_sd(x, length, tau_hl)
Exponentially Weighted Moving Standard Deviation.
ewm_scoring(x, length, tau_hl)
ewm_scoring
description Exponentially Weighted Moving Standardization:
發行說明
v3Added:
rationalQuadratic(_src, _lookback, _relativeWeight, startAtBar)
Rational Quadratic Kernel - An infinite sum of Gaussian Kernels of different length scales.
description from trader jdehorty KernelFunctions v2
Parameters:
_src (float): <float series> The source series.
_lookback (simple int): <simple int> The number of bars used for the estimation. This is a sliding value that represents the most recent historical bars.
_relativeWeight (simple float): <simple float> Relative weighting of time frames. Smaller values resut in a more stretched out curve and larger values will result in a more wiggly curve. As this value approaches zero, the longer time frames will exert more influence on the estimation. As this value approaches infinity, the behavior of the Rational Quadratic Kernel will become identical to the Gaussian kernel.
startAtBar (simple int)
Returns: yhat <float series> The estimated values according to the Rational Quadratic Kernel.
discreteFourierTransform(source, length, smoothing)
Discrete Fourier transform
description from trader jdehorty
Parameters:
source (float): time series
length (int)
smoothing (simple int)
Returns: a touple [dft, dfts] i.e. [Discrete Fourier Transform, Smoothed Discrete Fourier Transform]
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Pine腳本庫
秉持TradingView一貫精神,作者已將此Pine代碼以開源函式庫形式發佈,方便我們社群中的其他Pine程式設計師重複使用。向作者致敬!您可以在私人專案或其他開源發表中使用此函式庫,但在公開發表中重用此代碼須遵守社群規範。
免責聲明
這些資訊和出版物並非旨在提供,也不構成TradingView提供或認可的任何形式的財務、投資、交易或其他類型的建議或推薦。請閱讀使用條款以了解更多資訊。