# Simple Moving Average

## Function Prototype

/* Simple Moving Average */
/* Type: overlay */
/* Input arrays: 1    Options: 1    Output arrays: 1 */
/* Inputs: real */
/* Options: period */
/* Outputs: sma */
int ti_sma_start(TI_REAL const *options);
int ti_sma(int size,
TI_REAL const *const *inputs,
TI_REAL const *options,
TI_REAL *const *outputs);

## Description

This documentation is still a work in progress. It has omissions, and it probably has errors too. If you see any issues, or have any general feedback, please get in touch.

The Simple Moving Average is one of the most common smoothing functions used on time series data.

It takes one parameter, the period n. Larger values for n will have a greater smoothing effect on the input data but will also create more lag.

It is calculated for each bar as the arithmetic mean of the previous n bars.

$$sma_{t} = \frac{1}{n} \sum_{i=0}^{n-1} in_{t-i}$$

## Example Usage

### Calling From C

/* Example usage of Simple Moving Average */
/* Assuming that 'input' is a pre-loaded array of size 'in_size'. */
TI_REAL *inputs[] = {input};
TI_REAL options[] = {5}; /* period */
TI_REAL *outputs[1]; /* sma */

/* Determine how large the output size is for our options. */
const int out_size = in_size - ti_sma_start(options);

/* Allocate memory for output. */
outputs[0] = malloc(sizeof(TI_REAL) * out_size); assert(outputs[0] != 0); /* sma */

/* Run the actual calculation. */
const int ret = ti_sma(in_size, inputs, options, outputs);
assert(ret == TI_OKAY);


### Calling From Lua (with Tulip Chart bindings)

-- Example usage of Simple Moving Average
sma = ti.sma(input, 5)


## Example Calculation

period = 5

dateinputsma
2005-11-0181.59
2005-11-0281.06
2005-11-0382.87
2005-11-0483.00
2005-11-0783.6182.43
2005-11-0883.1582.74
2005-11-0982.8483.09
2005-11-1083.9983.32
2005-11-1184.5583.63
2005-11-1484.3683.78
2005-11-1585.5384.25
2005-11-1686.5484.99
2005-11-1786.8985.57
2005-11-1887.7786.22
2005-11-2187.2986.80

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