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Regression

Colorful RegressionColorful Regression is a trend indicator. The most important difference of it from other moving averages and regressions is that it can change color according to the momentum it has. so that users can have an idea about the direction, orientation and speed of the graph at the same time. This indicator contains 5 different colors. Black means extreme downtrend, red means downtrend, yellow means sideways trend, green means uptrend, and white means extremely uptrend. I recommend using it on the one hour chart. You can also use it in different time periods by changing the sensitivity settings.
อินดิเคเตอร์ Pine Script™
โดย faytterro
8
Everything Bitcoin [Kioseff Trading]Hello! This script retrieves most of the available Bitcoin data published by Quandl; the script utilizes the new request.security_lower_tf() function. Included statistics, True price Volume Difficulty My Wallet # Of Users Average Block Size api.blockchain size Median Transaction Confirmation Time Miners' Revenue Hash Rate Cost Per Transaction Cost % of Transaction Volume Estimated Transaction Volume USD Total Output Volume Number Of Transactions Per Block # of Unique BTC Addresses # of BTC Transactions Excluding Popular Addresses Total Number of Transactions Daily # of Transactions Total Transaction Fees USD Market Cap Total BTC Retrieved data can be plotted as line graphs; however, the data is initially split between two tables. The image above shows how the requested Bitcoin data is displayed. However, in the user inputs tab, you can modify how the data is displayed. For instance, you can append the data displayed in the floating statistics box to the stagnant statistics box. The image above exemplifies the instance. You can hide any and all data via the user inputs tab. In addition to data publishing, the script retrieves lower timeframe price/volume/indicator data, to which the values of the requested data are appended to center-right table. The image above shows the script retrieving one-minute bar data. Up arrows reflect an increase in the more recent value, relative to the immediately preceding value. Down arrows reflect a decrease in the more recent value relative to the immediately preceding value. The ascending minute column reflects the number of minutes/hours (ago) the displayed value occurred. For instance, 15 minutes means the displayed value occurred 15 minutes prior to the current time (value). Volume, price, and indicator data can be retrieved on lower timeframe charts ranging from 1 minute to 1440 minutes. The image above shows retrieved 5-minute volume data. Several built-in indicators are included, to which lower timeframe values can be retrieved. The image above shows LTF VWAP data. Also distinguished are increases/decreases for sequential values. The image above shows a dynamic regression channel. The channel terminates and resets each fiscal quarter. Previous channels remain on the chart. Lastly, you can plot any of the requested data. The new request.security_lower_tf() function is immensely advantageous - be sure to try it in your scripts!
อินดิเคเตอร์ Pine Script™
โดย KioseffTrading
32
Relative slopeRelative slope metric Description: I was in need to create a simple, naive and elegant metric that was able to tell how strong is the trend in a given rolling window. While abstaining from using more complicated and arguably more precise approaches, I’ve decided to use Linearly Weighted Linear Regression slope for this goal. Outright values are useful, but the problem was that I wasn’t able to use it in comparative analysis, i.e between different assets & different resolutions & different window sizes, because obviously the outputs are scale-variant. Here is the asset-agnostic, resolution-agnostic and window size agnostic version of the metric. I made it asset agnostic & resolution agnostic by including spread information to the formula. In our case it's weighted stdev over differenced data (otherwise we contaminate the spread with the trend info). And I made it window size agnostic by adding a non-linear relation of length to the output, so finally it will be aprox in (-1, 1) interval, by taking square root of length, nothing fancy. All these / 2 and * 2 in unexpected places all around the formula help us to return the data to it’s natural scale while keeping the transformations in place. Peace TV
อินดิเคเตอร์ Pine Script™
โดย gorx1
5
StrengthA mathematically elegant, native & modern way how to measure velocity/ strength/ momentum. As you can see it looks like MACD, but !suddenly! has N times shorter code (disregard the functions), and only 1 parameter instead of 3. OMG HOW DID HE DO IT?!? MACD: "Let's take one filter (1 parameter), than another filter (2 parameters), then let's take dem difference, then let's place another filter over the difference (3rd parameter + introduction of a nested calculation), and let's write a whole book about it, make thousands of multi-hours YouTube videos about it, and let's never mention about the amount of uncertainty being introduced by multiple parameters & introduction of the nested calculation." Strength: "let's get real, let's drop a weighted linear regression & usual linear regression over the data of the same length, take dem slopes, then make the difference over these slopes, all good. And then share it with people w/o putting an ® sign". Fyi, regressions were introduced centuries ago, maybe decades idk, the point is long time ago, and computational power enough to calculate what I'm saying is slightly more than required for macd. Rationale. Linearly weighted linear regression has steeper slope (W) than the usual linear regression slope (S) due to the fact that the recent datapoints got more weight. This alone is enough of a metric to measure velocity. But still I've recalled macd and decided to make smth like it cuz I knew it'll might make you happy. I realized that S can be used instead of smoothing the W, thus eliminating the nested calculation and keeping entropy & info loss in place. And see, what we get is natural, simple, makes sense and brings flex. I also wanna remind you that by applying regression we maximize the info gain by using all the data in the window, instead of taking difference between the first and the last datapoints. This script is dedicated to my friend Fabien. Man, you were the light in the darkness in that company. You'll get your alien green Lambo if you'll really want it, no doubts on my side bout that. Good hunting
อินดิเคเตอร์ Pine Script™
โดย gorx1
14
Weighted Least Squares Moving AverageLinearly Weighted Ordinary Least Squares Moving Regression aka Weighted Least Squares Moving Average -> WLSMA ^^ called it this way just to for... damn, forgot the word Totally pwns LSMA for some purposes here's why (just look up): - 'realistically' the same smoothness; - less lag; - less overshoot; - more or less same computationally intensive. "Pretty cool, huh?", Bucky Roberts©, thenewboston Now, would you please (just look down) and see the comparison of impulse & step responses: Impulse responses Step responses Ain't it beautiful? "Motivation behind the concept & rationale", by gorx1 Many been trippin' applying stats methods that require normally distributed data to time series, hence all these B*ll**** Bands and stuff don't really work as it should, while people blame themselves and buy snake oil seminars bout trading psychology, instead of using proper tools. Price... Neither population nor the samples are neither normally nor log-normally distributed. So we can't use all the stuff if we wanna get better results. I'm not talking bout passing each rolling window to a stat test in order to get the proper descriptor, that's the whole different story. Instead we can leverage the fact that our data is time-series hence we can apply linear weighting, basically we extract another info component from the data and use it to get better results. Volume, range weighting don't make much sense (saying that based on both common sense and test results). Tick count per bar, that would be nice tho... this is the way to measure "intensity". But we don't have it on TV unfortunately. Anyways, I'm both unhappy that no1 dropped it before me during all these years so I gotta do it myself, and happy that I can give smth cool to every1 Here is it, for you. P.S.: the script contains standalone functions to calculate linearly weighted variance, linearly weighted standard deviation, linearly weighted covariance and linearly weighted correlation. Good hunting
อินดิเคเตอร์ Pine Script™
โดย gorx1
8
Linear Regression Channel - Auto Volume BasedBased on oryginal TV indicator BUT with a little twist. ;) I really like the regression channel - but the problem is that the length needs to be always manually adjusted. In this script I try to solve this issue. This is modified version on TV indicator - Linear Regression Channel. The main difference is that now you don't get static length - it is automatically adjuested to the recent price action (determined by highest volume in last 300 bars).
อินดิเคเตอร์ Pine Script™
โดย okhanLAB
9
Linear Regression Relative Strength[image/x/iZvwDWEY/ Relative Strength indicator comparing the current symbol to SPY (or any other benchmark). It may help to pick the right assets to complement the portfolio build around core ETFs such as SPY. The general idea is to show if the current symbol outperforms or underperforms the benchmark (SPY by default) when bought some certain time ago. Relative performance is displayed as percent and is calculated for three different time ranges - short (1 mo by default), mid (1 quarter), and long (half a year). To smooth the volatility, the script uses linear regression to estimate the trend and takes the start and the end points of the linear regression line to compute the relative strength. It is important to remember that the script shows the gain relative to SPY (or other selected benchmark), not the asset's gain. Therefore, it may indicate that the asset is profitable, but it still may lose value if SPY is in downtrend. Therefore, it is crucial to check other indicators before making a decision. In the example above, standard linear regression for one quarter is used to indicate the direction of the trend.
อินดิเคเตอร์ Pine Script™
โดย gaperton
2
vix_vx_regressionAn example of the linear regression library, showing the regression of VX futures on the VIX. The beta might help you weight VX futures when hedging SPX vega exposure. A VX future has point multiplier of 1000, whereas SPX options have a point multiplier of 100. Suppose the front month VX future has a beta of 0.6 and the front month SPX straddle has a vega of 8.5. Using these approximations, the VX future will underhedge the SPX straddle, since (0.6 * 1000) < (8.5 * 100). The position will have about 2.5 ($250) vega. Use the R^2 (coefficient of determination) to check how well the model fits the relationship between VX and VIX. The further from one this value, the less useful the model. (Note that the mini, VXM futures also have a 100 point multiplier).
อินดิเคเตอร์ Pine Script™
โดย taylor_o
Universal logarithmic growth curves, with support and resistanceLogarithmic regression is used to model data where growth or decay accelerates rapidly at first and then slows over time. This model is for the long term series data (such as 10 years time span). The user can consider entering the market when the price below 25% or 5% confidence and consider take profit when the price goes above 75% or 95% confidence line. This script is: - Designed to be usable in all tickers. (not only for bitcoin now!) - Logarithmic regression and shows support-resistance level - Shape of lines are all linear adjustable - Height difference of levels and zones are customizable - Support and resistance levels are highlighted Input panel: - Steps of drawing: Won't change it unless there are display problems. - Resistance, support, other level color: self-explanatory. - Stdev multipliers: A constant variable to adjust regression boundaries. - Fib level N: Base on the relative position of top line and base line. If you don't want all fib levels, you might set all fib levels = 0.5. - Linear lift up: vertically lift up the whole set of lines. By linear multiplication. - Curvature constant: It is the base value of the exponential transform before converting it back to the chart and plotting it. A bigger base value will make a more upward curvy line. FAQ: Q: How to use it? A: Click "Fx" in your chart then search this script to get it into your chart. Then right click the price axis, then select "Logarithmic" scale to show the curves probably. Q: Why release this script? A: - This script is intended to to fix the current issues of bitcoins growth curve script, and to provide a better version of the logarithmic curve, which is not only for bitcoin , but for all kinds of tickers. - In the public library there is a hardcoded logarithmic growth curve by @quantadelic . But unfortunately that curve was hardcoded by his manual inputs, which makes the curve stop updating its value since 2019 the date he publish that code. Many users of that script love using it but they realize it was stop updating, many users out there based on @quantadelic version of "bitcoin logarithmic growth curves" and they tried their best to update the coordinates with their own hardcode input values. Eventually, a lot of redundant hardcoded "Bitcoin growth curve" scripts was born in the public library. Which is not a good thing. Q: What about looking at the regression result with a log scale price axis? A: You can use this script that I published in a year ago. This script display the result in a log scale price axis.
อินดิเคเตอร์ Pine Script™
โดย BillionaireLau
15
Ripple (XRP) Model PriceAn article titled Bitcoin Stock-to-Flow Model was published in March 2019 by "PlanB" with mathematical model used to calculate Bitcoin model price during the time. We know that Ripple has a strong correlation with Bitcoin. But does this correlation have a definite rule? In this study, we examine the relationship between bitcoin's stock-to-flow ratio and the ripple(XRP) price. The Halving and the stock-to-flow ratio Stock-to-flow is defined as a relationship between production and current stock that is out there. SF = stock / flow The term "halving" as it relates to Bitcoin has to do with how many Bitcoin tokens are found in a newly created block. Back in 2009, when Bitcoin launched, each block contained 50 BTC, but this amount was set to be reduced by 50% every 210,000 blocks (about 4 years). Today, there have been three halving events, and a block now only contains 6.25 BTC. When the next halving occurs, a block will only contain 3.125 BTC. Halving events will continue until the reward for minors reaches 0 BTC. With each halving, the stock-to-flow ratio increased and Bitcoin experienced a huge bull market that absolutely crushed its previous all-time high. But what exactly does this affect the price of Ripple? Price Model I have used Bitcoin's stock-to-flow ratio and Ripple's price data from April 1, 2014 to November 3, 2021 (Daily Close-Price) as the statistical population. Then I used linear regression to determine the relationship between the natural logarithm of the Ripple price and the natural logarithm of the Bitcoin's stock-to-flow (BSF). You can see the results in the image below: Basic Equation : ln(Model Price) = 3.2977 * ln(BSF) - 12.13 The high R-Squared value (R2 = 0.83) indicates a large positive linear association. Then I "winsorized" the statistical data to limit extreme values to reduce the effect of possibly spurious outliers (This process affected less than 4.5% of the total price data). ln(Model Price) = 3.3297 * ln(BSF) - 12.214 If we raise the both sides of the equation to the power of e, we will have: ============================================ Final Equation: ■ Model Price = Exp(- 12.214) * BSF ^ 3.3297 Where BSF is Bitcoin's stock-to-flow ============================================ If we put current Bitcoin's stock-to-flow value (54.2) into this equation we get value of 2.95USD. This is the price which is indicated by the model. There is a power law relationship between the market price and Bitcoin's stock-to-flow (BSF). Power laws are interesting because they reveal an underlying regularity in the properties of seemingly random complex systems. I plotted XRP model price (black) over time on the chart. Estimating the range of price movements I also used several bands to estimate the range of price movements and used the residual standard deviation to determine the equation for those bands. Residual STDEV = 0.82188 ln(First-Upper-Band) = 3.3297 * ln(BSF) - 12.214 + Residual STDEV => ln(First-Upper-Band) = 3.3297 * ln(BSF) – 11.392 => ■ First-Upper-Band = Exp(-11.392) * BSF ^ 3.3297 In the same way: ■ First-Lower-Band = Exp(-13.036) * BSF ^ 3.3297 I also used twice the residual standard deviation to define two extra bands: ■ Second-Upper-Band = Exp(-10.570) * BSF ^ 3.3297 ■ Second-Lower-Band = Exp(-13.858) * BSF ^ 3.3297 These bands can be used to determine overbought and oversold levels. Estimating of the future price movements Because we know that every four years the stock-to-flow ratio, or current circulation relative to new supply, doubles, this metric can be plotted into the future. At the time of the next halving event, Bitcoins will be produced at a rate of 450 BTC / day. There will be around 19,900,000 coins in circulation by August 2025 It is estimated that during first year of Bitcoin (2009) Satoshi Nakamoto (Bitcoin creator) mined around 1 million Bitcoins and did not move them until today. It can be debated if those coins might be lost or Satoshi is just waiting still to sell them but the fact is that they are not moving at all ever since. We simply decrease stock amount for 1 million BTC so stock to flow value would be: BSF = (19,900,000 – 1.000.000) / (450 * 365) =115.07 Thus, Bitcoin's stock-to-flow will increase to around 115 until AUG 2025. If we put this number in the equation: Model Price = Exp(- 12.214) * 114 ^ 3.3297 = 36.06$ Ripple has a fixed supply rate. In AUG 2025, the total number of coins in circulation will be about 56,000,000,000. According to the equation, Ripple's market cap will reach $2 trillion. Note that these studies have been conducted only to better understand price movements and are not a financial advice.
อินดิเคเตอร์ Pine Script™
โดย BobRivera990
9
Nadaraya-Watson Envelope [LuxAlgo]This indicator builds upon the previously posted Nadaraya-Watson smoothers. Here we have created an envelope indicator based on Kernel Smoothing with integrated alerts from crosses between the price and envelope extremities. Unlike the Nadaraya-Watson estimator, this indicator follows a contrarian methodology. Please note that by default this indicator can be subject to repainting. Users can use a non-repainting smoothing method available from the settings. The triangle labels are designed so that the indicator remains useful in real-time applications. 🔶 USAGE 🔹 Non Repainting This tool can outline extremes made by the prices. This is achieved by estimating the underlying trend in the price, then calculating the mean absolute deviations from it, the obtained result is added/subtracted to the estimated underlying trend. The non-repainting method estimates the underlying trend in price using an "endpoint Nadaraya-Watson estimator", and would return similar results to more classical band indicators. 🔹 Repainting The repainting method makes use of the Nadaraya-Watson estimator to estimate the underlying trend in the price. The construction of the band extremities is the same as in the non-repainting method. We can expect the price to reverse when crossing one of the envelope extremities. Crosses between the price and the envelopes extremities are indicated with triangles on the chart. For real-time applications, triangles are always displayed when a cross occurs and remain displayed at the location it first appeared even if the cross is no longer visible after a recalculation of the envelope. By popular demand, we have integrated alerts for this indicator from the crosses between the price and the envelope extremities. However, we do not recommend this precise method to be used alone or for solely real-time applications. We do not have data supporting the performance of this tool over more classical bands/envelope/channels indicators. 🔶 SETTINGS Bandwidth: Controls the degree of smoothness of the envelopes, with higher values returning smoother results. Mult: Controls the envelope width. Source: Input source of the indicator. Repainting Smoothing: Determine if a repainting or non-repainting method should be used for the calculation of the indicator. 🔶 RELATED SCRIPTS For more information on the Nadaraya-Watson estimator see:
อินดิเคเตอร์ Pine Script™
โดย LuxAlgo
540
Nadaraya-Watson Smoothers [LuxAlgo]The following tool smoothes the price data using various methods derived from the Nadaraya-Watson estimator, a simple Kernel regression method. This method makes use of the Gaussian kernel as a weighting function. Users have the option to use a non-repainting as well as a repainting method, see the USAGE section for more information. 🔶 USAGE 🔹 Non Repainting When Repainting Smoothing is disabled the returned indicator acts similarly to a regular causal moving average. This result could be described as an "endpoint Nadaraya-Watson estimator". Unlike a regular moving average whose degree of smoothness is commonly determined by the length of its calculation window, the degree of smoothness of the proposed indicator is determined by the bandwidth setting, with a higher value returning smoother results. In the above chart, a bandwidth value of 50 is used. An increasing value of the smoother is indicative of an uptrend, while a decreasing value is indicative of a downtrend. 🔹 Repainting Non-causal smoothing methods have found low support from technical analysts because they tend to repaint. Yet, they can provide powerful insights such as estimating underlying trends in the price as well as seeing how far prices deviate from them. They can also make drawing certain patterns easier and can help see underlying structures in the price more clearly. Using higher bandwidth values allows for estimating longer-term trends in the price. Triangular labels highlight points where the direction of the estimator change. This allows for the identification of tops and bottoms in the underlying trend which can be compared to the actual price tops and bottoms. Note that multiple labels can appear in real time, highlighting real-time changes in the estimator's direction. The most recent label on a series of labels is the first to appear. This can eventually be useful for the real-time predictive application of the estimator. However, it is not a usage we particularly recommend. 🔶 DETAILS The Nadaraya-Watson estimator can be described as a series of weighted averages using a specific normalized kernel as a weighting function. For each point of the estimator at time t , the peak of the kernel is located at time t , as such the highest weights are attributed to values neighboring the price located at time t . A lower bandwidth value would contribute toward a more important weighting of the price at a precise point and would as such less smooth results. In the case where our bandwidth is so small that the resulting kernel is just an impulse, we would get the raw price back. However, when the bandwidth is sufficiently large, prices would be weighted similarly, thus resulting in a result closer to the price mean. It can be interesting to note that due to the nature of the estimator and its weighting procedure, real-time results would not deviate drastically for points in the estimator near the center of the calculation window. 🔶 SETTINGS Bandwidth : controls the bandwidth of the Gaussian kernel, with higher values returning smoother results. Src : Input source of the kernel regression. Repainting Smoothing : Determine if the smoothing method should repaint or not. If disabled the "endpoint Nadaraya-Watson estimator" is returned.
อินดิเคเตอร์ Pine Script™
โดย LuxAlgo
249
Linear Regression & RSI Multi-Function Screener with Table-LabelHi fellow traders.. Happy to share a Linear Regression & RSI Multi-Function Custom Screener with Table-Labels... The Screener scans for Linear Regression 2-SD Breakouts and RSI OB/OS levels for the coded tickers and gives Summary alerts Uses Tables (dynamica resizing) for the scanner output instead of standard labels! This Screener cum indicator collection has two distinct objectives.. 1. Attempt re-entry into trending trades. 2. Attempt Counter trend trades using linear regression , RSI and Zigzag. Briefly about the Screener functions.. a. It uses TABLES as Labels a FIRST for any Screener on TV. b. Tables dynamically resize based on criteria.. c. Alerts for breakouts of the UPPER and the LOWER regression channels.(2 SD) d. In addition to LinReg it also Screens RSI for OB/OS levels so a multifunction Screener. e. Of course has the standard summary Alerts and programmable format for Custom functions. f. Uses only the inbuilt Auto Fib and Lin Reg code for the screener.(No proprietary stuff) g. The auto Zigzag code is derived(Auto fib). Question what are all these doing in a single screener ?? ZigZag is very useful in determining Trend Up or Down from one Pivot to another. So Once you have a firm view of the Current Trend for your chosen timeframe and ticker… We can consider few possible trading scenarios.. a. Re-entry in an Up Trend - Combination of OS Rsi And a Lower Channel breach followed by a re-entry back into the regression channel CAN be used as an effective re-entry. b. Similarily one can join a Down Trend on OB Rsi and Upper Channel line breach followed by re-entry into the regression channel. If ZigZag signals a range-bound market, bound within channel lines then the Upper breakout can be used to Sell and vice-versa! In short many possibilities for using these functions together with Scanner and Alerts. This facilitates timely PROFITABLE Trending and Counter trend opportunities across multiple tickers. You must give a thorough READ to the various available tutorials on ZigZag / Regression and Fib retracements before attempting counter trend trades using these tools!! A small TIP – Markets are sideways or consolidating 70% of the time!! Acknowledgements: - Thanks a lot DGTRD for the Auto ZigZag code and also for the eagerness to help wherever possible..Respect!! Disclaimer: The Alerts and Screener are just few tools among many and not any kind of Buy/Sell recommendations. Unless you have sufficient trading experience please consult a Financial advisor before investing real money. *The alerts are set for crossovers however for viewing tickers trading above or below the channel use code in line 343 and 344 after setting up the Alerts! ** RSI alerts are disabled by default to avoid clutter, but if needed one can activate code lines 441,442,444 and 445 Wish you all, Happy Profitable Trading!
อินดิเคเตอร์ Pine Script™
โดย sharaaU7
19
Robust Channel [tbiktag]Introducing the Robust Channel indicator. This indicator is based on a remarkable property of robust statistics , namely, the resistance​ to the presence of data points that deviate significantly from the established trend (generally speaking, outliers ). Being outlier-resistant, the Robust Channel indicator “remembers” a pre-existing trend and thus exhibits a very peculiar "lag" in case of a sharp price change. This allows high-confidence identification of such price actions as a trend reversal, range break, pullback, etc. In the case of trending and range-bound market conditions, the price remains within the channel most of the time, fluctuating around the central line. Technical details The central line is calculated using the repeated median slope algorithm. For each data point in a lookback window of a user-specified Length , this method calculates the median slope of the lines that connect that point to all other points inside the window. The overall median of these median slopes is then calculated and used as an estimate of the trend slope. The algorithm is very efficient as it uses an on-the-fly procedure to update the array containing the slopes (new data pushed - old data removed). The outer line is then calculated as the central line plus the Length -period standard deviation of the price data multiplied by a user-defined Channel Width Factor . The inner line is defined analogously below the central line. Usage As a stand-alone indicator, the Robust Channel can be applied similarly to the Bollinger Bands and the Keltner Channel: A close above the outer line can be interpreted as a bullish signal and a close below the inner line as a bearish signal. Likewise, a return to the channel from below after a break may serve as a bullish signal, while a return from above may indicate bearish sentiment. Robust Channel can be also used to confirm chart patterns such as double tops and double bottoms. If you like this indicator, feel free to leave your feedback in the comments below!
อินดิเคเตอร์ Pine Script™
โดย tbiktag
14
Matrix Library (Linear Algebra, incl Multiple Linear Regression)What's this all about? Ever since 1D arrays were added to Pine Script, many wonderful new opportunities have opened up. There has been a few implementations of matrices and matrix math (most notably by TradingView-user tbiktag in his recent Moving Regression script: ). However, so far, no comprehensive libraries for matrix math and linear algebra has been developed. This script aims to change that. I'm not math expert, but I like learning new things, so I took it upon myself to relearn linear algebra these past few months, and create a matrix math library for Pine Script. The goal with the library was to make a comprehensive collection of functions that can be used to perform as many of the standard operations on matrices as possible, and to implement functions to solve systems of linear equations. The library implements matrices using arrays, and many standard functions to manipulate these matrices have been added as well. The main purpose of the library is to give users the ability to solve systems of linear equations (useful for Multiple Linear Regression with K number of independent variables for example), but it can also be used to simulate 2D arrays for any purpose. So how do I use this thing? Personally, what I do with my private Pine Script libraries is I keep them stored as text-files in a Libraries folder, and I copy and paste them into my code when I need them. This library is quite large, so I have made sure to use brackets in comments to easily hide any part of the code. This helps with big libraries like this one. The parts of this script that you need to copy are labeled "MathLib", "ArrayLib", and "MatrixLib". The matrix library is dependent on the functions from these other two libraries, but they are stripped down to only include the functions used by the MatrixLib library. When you have the code in your script (pasted somewhere below the "study()" call), you can create a matrix by calling one of the constructor functions. All functions in this library start with "matrix_", and all constructors start with either "create" or "copy". I suggest you read through the code though. The functions have very descriptive names, and a short description of what each function does is included in a header comment directly above it. The functions generally come in the following order: Constructors: These are used to create matrices (empy with no rows or columns, set shape filled with 0s, from a time series or an array, and so on). Getters and setters: These are used to get data from a matrix (like the value of an element or a full row or column). Matrix manipulations: These functions manipulate the matrix in some way (for example, functions to append columns or rows to a matrix). Matrix operations: These are the matrix operations. They include things like basic math operations for two indices, to transposing a matrix. Decompositions and solvers: Next up are functions to solve systems of linear equations. These include LU and QR decomposition and solvers, and functions for calculating the pseudo-inverse or inverse of a matrix. Multiple Linear Regression: Lastly, we find an implementation of a multiple linear regression, including all the standard statistics one can expect to find in most statistical software packages. Are there any working examples of how to use the library? Yes, at the very end of the script, there is an example that plots the predictions from a multiple linear regression with two independent (explanatory) X variables, regressing the chart data (the Y variable) on these X variables. You can look at this code to see a real-world example of how to use the code in this library. Are there any limitations? There are no hard limiations, but the matrices uses arrays, so the number of elements can never exceed the number of elements supported by Pine Script (minus 2, since two elements are used internally by the library to store row and column count). Some of the operations do use a lot of resources though, and as a result, some things can not be done without timing out. This can vary from time to time as well, as this is primarily dependent on the available resources from the Pine Script servers. For instance, the multiple linear regression cannot be used with a lookback window above 10 or 12 most of the time, if the statistics are reported. If no statistics are reported (and therefore not calculated), the lookback window can usually be extended to around 60-80 bars before the servers time out the execution. Hopefully the dev-team at TradingView sees this script and find ways to implement this functionality diretly into Pine Script, as that would speed up many of the operations and make things like MLR (multiple linear regression) possible on a bigger lookback window. Some parting words This library has taken a few months to write, and I have taken all the steps I can think of to test it for bugs. Some may have slipped through anyway, so please let me know if you find any, and I'll try my best to fix them when I have time to do so. This library is intended to help the community. Therefore, I am releasing the library as open source, in the hopes that people may improving on it, or using it in their own work. If you do make something cool with this, or if you find ways to improve the code, please let me know in the comments.
อินดิเคเตอร์ Pine Script™
โดย lejmer
21