Calculates the min value of all the elements in the input array, or the min value of every N successive elements in the input array. 

Calculates the max value of all the elements in the input array, or the max value of every N successive elements in the input array. 

This function calculates the median value for the data in the 'values' array. The median is the middle value in a distribution, above and below which lie an equal number of values. 

The function calculates the cumulative sum of the elements in the input array. Each element of the result is equal to the previous element of the result plus the current element of the input array. 

Calculates the sum of all the elements in the input array, or the sum of every N successive elements in the input array. 

Calculates the average of the elements in the input array, or the average of every N successive elements in the input array. 

The function calculates the exponential average of the input array. The formula is:
Result[n] = arg1[n] * weight + arg1[n1] * (1  weight) 

The Root Mean Square (RMS), also known as the quadratic mean, is a statistical measure of the magnitude of a varying quantity. It can be calculated for a series of discrete values or for a continuously varying function. Its name comes from its definition as the square root of the mean of the squares of the values. 

Standard deviation is used to indicate volatility. It measures the difference between values (Closing Price) and average. If the difference is larger, the standard deviation and volatility are higher. If the value (Closing price) is closer to the average price, the standard deviation and volatility are lower. 

Calculates the linear regression of the master series values. The calculation takes into account the X values of master series. If the master series is an XY scatter, you have the option to control whether the regression line is draw from the min to max X value (if UseXMinMax is checked) or from the first to the last item in the data set. 

    Calculates the polynomial regression of the master series values. The calculation takes into account the X values of master series. You have the option to control the polynomial order and thus create polynomial interpolations of second, third and higher degrees. 
    


Bollinger Bands are indicators that are plotted at standard deviation levels above and below a simple moving average. Since standard deviation is a measure of volatility, a large standard deviation is a good indicator for a volatile market, while a smaller standard deviation is an indicator of a calmer market.
Bollinger Bands are a good way to compare volatility and relative price levels over a period of time. 

Envelopes are plotted above and below a moving average using a specified percentage. The Envelopes indicator is used to create signals for buying and selling. The percentage which will be used for calculating envelopes is specified by user and it depends on volatility of the market. If the market is more volatile the percentage is higher. 

A Simple Moving Average is an average of data calculated over a period of time. The moving average is the most popular price indicator used in technical analyses, and can be used with any price: Hi, Low, Open, Close or it could be applied to other indicators. Moving average smoothes a data series which is very important in a volatile market. With a moving average it is much easier to spot a trend.  


A Weighted Moving Average is the average of the data calculated over a period of time where the greater weights are attached to the most recent data. The weighting is calculated from the sum of days. The Weighted Moving Average can be used with any price: Hi, Low, Open, Close or it could be applied to other indicators. Weighted Moving Average smoothes a data series which is very important in a volatile market.  


A Exponential Moving Average is an average of data calculated over a period of time where the most recent days have more weight. The exponential moving average can be used with any price: Hi, Low, Open, Close or it could be applied to other indicators. Exponential Moving average smoothes out data series, which is very important in a volatile market.
Nevron Chart has four types of moving averages: Simple, Weighted, Exponential and Modified. The most important difference between the various moving averages is how weights are applied.  


Modified Moving Average (MMA) is a type of exponential moving average (EMA) where the weight given to older records decreases exponentially.  


Median price is the midpoint value of daily prices. Median price can be used as a filter for trend indicators. It is also used as the daily average price which is very useful if we want a simpler view of prices.  


Typical price is the average value of daily prices. Typical price can be used as a filter for trend indicators as well as the daily average price which is very useful if we want a simpler view of prices.  


Weighted Close formula calculates the average value of daily prices. The only difference between Typical Price and Weighted Close is that the closing price has extra weight as the most important price. Weighted Close could be used as a filter for trend indicators, as well as being used as the daily average price which is very useful if we want a simpler view of prices.  


The Positive Direction Indicator (+DI) summarizes upward trend movement.
The Positive Direction Indicator is a component of the average directional index that is used to measure the presence of an uptrend. When the +DI is sloping upward, it is a signal that the uptrend is getting stronger. This indicator is nearly always plotted along with the negative directional indicator.  


The Negative Direction Indicator (DI) summarizes downward trend movement.
The Negative Direction Indicator is a component of the average directional index (ADX) that is used to measure the presence of a downtrend. When the DI is sloping upward, it is a signal that the strength of the downtrend is increasing. This indicator is almost always plotted with the positive directional indicator (+DI).  


The Directional Movement Index (DMI) helps identify whether there is a definable trend in a market, and in which direction that trend is moving. The ADX function, which is a part of the Directional Movement System, is based on the DMI.  
