[
    {
        "name": "Linear",
        "comment": " Contains functions to create a linear forecast, i. e. a simple trend line.\n\n@docs regression, forecast\n",
        "unions": [],
        "aliases": [],
        "values": [
            {
                "name": "forecast",
                "comment": " Creates a list of tuples with forecasted values. The first parameter indicates how many values.\n\nPlease note that this function expects to get a sorted list of points. It will create a range based on the last point. \n\n    vals = [(0, 0), (0.5, 0.25), (1, 0.5), (3, 1.5)]\n    \n    forecast 3 vals == [(4, 2), (5, 2.5), (6, 3)]\n",
                "type": "Int -> List ( Float, Float ) -> List ( Float, Float )"
            },
            {
                "name": "regression",
                "comment": " Expects a list of Float-tuples, where the first element is the x- and the second element is the y-coordinate of a point. It returns a linear function, that gets a Float and emits new values.\n\n    vals = [(0, 0), (1, 0.5), (2, 1), (3, 1.5)]\n    regressionFunction = regression vals\n\n    regressionFunction 4 == 2\n",
                "type": "List ( Float, Float ) -> Float -> Float"
            }
        ],
        "binops": []
    },
    {
        "name": "Seasonal",
        "comment": " Contains functions to create a seasonal forecast based on the Holt-Winters method for seasonal forecasting.\r\n\r\n@docs forecast, forecastWith\r\n",
        "unions": [],
        "aliases": [],
        "values": [
            {
                "name": "forecast",
                "comment": " Creates a forecast with default parameters (alpha = 0.5, beta = 0.4, gamma = 0.6, number of forecasted values = length of period). You only need to specify the length of a season (number of values per season). \r\n",
                "type": "Int -> List Float -> Maybe (List Float)"
            },
            {
                "name": "forecastWith",
                "comment": " Creates a seasonal forecast. Set the following parameters:\r\n\r\n* alpha: overall smoothing parameter (between 0 and 1)\r\n* beta: seasonal smoothing parameter (between 0 and 1)\r\n* gamma: trend smoothing parameter (between 0 and 1)\r\n* m: number of values to forecast (between 0 and period)\r\n* period: values per season (length of period) in the historical data\r\n* data: list of float values with historical data\r\n",
                "type": "Float -> Float -> Float -> Int -> Int -> List Float -> Maybe (List Float)"
            }
        ],
        "binops": []
    }
]