Translation components API.

See the Weblate's Web API documentation for detailed description of the API.

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                "If A3 contains an expression equivalent to the division by zero, the function returns 2, because 2 is the index number of the error value #DIV/0!"
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                "More advanced way"
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                "If in division A1 by A2, A2 can turn to zero, you can handle the situation as follows:"
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                "<item type=\"input\">=IF(ISERROR(A1/A2);IF(ERROR.TYPE(A1/A2)=2;\"the denominator can't be equal to zero\");A1/A2)</item>"
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                "The ISERROR function returns TRUE or FALSE depending on whether there is an error or not. If the error takes place, the function IF addresses to the second argument, if there is no error, it returns the result of the division. The second argument checks the index number representing the specific Error type, and if it is equal to 2, it returns the specified text \"the denominator can't be zero\" or 0 otherwise. Thus, clear text would signify the division by zero, the result of the division would appear when the division is successful, or if there is, for example, an error of another type, zero would be returned."
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                "If the ERROR.TYPE function is used as condition of the IF function and the ERROR.TYPE returns #N/A, the IF function returns #N/A as well. Use ISERROR to avoid it as shown in the example above."
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                "<link href=\"text/scalc/01/04060104.xhp#iserror\">ISERROR</link>, <link href=\"text/scalc/01/04060104.xhp#na\">NA</link>, <link href=\"text/scalc/01/04060104.xhp#Section4\">IF</link>"
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                "<bookmark_value>FORECAST.ETS.ADD function</bookmark_value>"
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                "<bookmark_value>KROĈI-funkcio</bookmark_value>"
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                "<link href=\"text/scalc/01/func_forecastetsadd.xhp\">FORECAST.ETS.ADD function</link>"
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                "<ahelp hid=\"HID_FUNC_FORECAST_ETS_ADD\">Calculates the additive forecast(s) (future values) based on the historical data using ETS or EDS algorithms</ahelp>. EDS is used when argument <emph>period_length</emph> is 0, otherwise ETS is used."
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                "FORECAST.ETS.ADD calculates with the model"
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                "FORECAST.ETS.ADD(targets, values, timeline, [period_length], [data_completion], [aggregation])"
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                "Returns 157.166666666667, the additive forecast for January 2014 based on <emph>Values</emph> and <emph>Timeline</emph> named ranges above, with one sample per period, no missing data, and AVERAGE as aggregation."
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            "source": [
                "Returns 113.251442038722, the additive forecast for January 2014 based on <emph>Values</emph> and <emph>Timeline</emph> named ranges above, with period length of 4, no missing data, and SUM as aggregation."
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            "source": [
                "See also:  <link href=\"text/scalc/01/func_forecastetsmult.xhp\">FORECAST.ETS.MULT</link>,  <link href=\"text/scalc/01/func_forecastetsstatadd.xhp\">FORECAST.ETS.STAT.ADD</link>,  <link href=\"text/scalc/01/func_forecastetsstatmult.xhp\">FORECAST.ETS.STAT.MULT</link>,  <link href=\"text/scalc/01/func_forecastetspiadd.xhp\">FORECAST.ETS.PI.ADD</link>,  <link href=\"text/scalc/01/func_forecastetspimult.xhp\">FORECAST.ETS.PI.MULT</link>,  <link href=\"text/scalc/01/func_forecastetsseason.xhp\">FORECAST.ETS.SEASONALITY</link>,  <link href=\"text/scalc/01/04060185.xhp#forecast\">FORECAST</link>,  <link href=\"text/scalc/01/04060185.xhp#forecastlinear\">FORECAST.LINEAR</link>"
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                "FORECAST.ETS.MULT"
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            "priority": 100,
            "id": 1504056,
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                "<bookmark_value>FORECAST.ETS.MULT function</bookmark_value>"
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                "<bookmark_value>PASKADIMANĈO-funkcio</bookmark_value>"
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                "<ahelp hid=\"HID_FUNC_FORECAST_ETS_MULT\">Calculates the multiplicative forecast(s) (future values) based on the historical data using ETS or EDS algorithms</ahelp>. EDS is used when argument <emph>period_length</emph> is 0, otherwise ETS is used."
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                "FORECAST.ETS.MULT calculates with the model"
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                "FORECAST.ETS.MULT(targets, values, timeline, [period_length], [data_completion], [aggregation])"
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                "=FORECAST.ETS.MULT(DATE(2014;1;1);Values;Timeline;1;TRUE();1)"
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            "source": [
                "Returns 131.71437427439, the multiplicative forecast for January 2014 based on <emph>Values</emph> and <emph>Timeline</emph> named ranges above, with one sample per period, no missing data, and AVERAGE as aggregation."
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                "=FORECAST.ETS.MULT(DATE(2014;1;1);Values;Timeline;4;TRUE();7)"
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            "id": 1504064,
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            "source": [
                "Returns 120.747806144882, the multiplicative forecast for January 2014 based on <emph>Values</emph> and <emph>Timeline</emph> named ranges above, with period length of 4, no missing data, and SUM as aggregation."
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                "See also:  <link href=\"text/scalc/01/func_forecastetsadd.xhp\">FORECAST.ETS.ADD</link>,  <link href=\"text/scalc/01/func_forecastetsstatadd.xhp\">FORECAST.ETS.STAT.ADD</link>,  <link href=\"text/scalc/01/func_forecastetsstatmult.xhp\">FORECAST.ETS.STAT.MULT</link>,  <link href=\"text/scalc/01/func_forecastetspiadd.xhp\">FORECAST.ETS.PI.ADD</link>,  <link href=\"text/scalc/01/func_forecastetspimult.xhp\">FORECAST.ETS.PI.MULT</link>,  <link href=\"text/scalc/01/func_forecastetsseason.xhp\">FORECAST.ETS.SEASONALITY</link>,  <link href=\"text/scalc/01/04060185.xhp#forecast\">FORECAST</link>,  <link href=\"text/scalc/01/04060185.xhp#forecastlinear\">FORECAST.LINEAR</link>"
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                "FORECAST.ETS.PI.ADD(target, values, timeline, [confidence_level], [period_length], [data_completion], [aggregation])"
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                "For example, with a 90% Confidence level, a 90% prediction interval will be computed (90% of future points are to fall within this radius from forecast)."
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                "Note on prediction intervals: there is no exact mathematical way to calculate this for forecasts, there are various approximations. Prediction intervals tend to be increasingly 'over-optimistic' when increasing distance of the forecast-X from the observation data set."
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                "For ETS, Calc uses an approximation based on 1000 calculations with random variations within the standard deviation of the observation data set (the historical values)."
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                "=FORECAST.ETS.PI.ADD(DATE(2014;1;1);Values;Timeline;0.9;1;TRUE();1)"
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                "Returns 18.8061295551355, the prediction interval for additive forecast for January 2014 based on <emph>Values</emph> and <emph>Timeline</emph> named ranges above, 90% (=0.9) confidence level, with one sample per period, no missing data, and AVERAGE as aggregation."
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                "Returns 23.4416821953741, the prediction interval for additive forecast for January 2014 based on <emph>Values</emph> and <emph>Timeline</emph> named ranges above, with confidence level of 0.8, period length of 4, no missing data, and SUM as aggregation."
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                "See also:  <link href=\"text/scalc/01/func_forecastetsadd.xhp\">FORECAST.ETS.ADD</link>,  <link href=\"text/scalc/01/func_forecastetsmult.xhp\">FORECAST.ETS.MULT</link>,  <link href=\"text/scalc/01/func_forecastetsstatadd.xhp\">FORECAST.ETS.STAT.ADD</link>,  <link href=\"text/scalc/01/func_forecastetsstatmult.xhp\">FORECAST.ETS.STAT.MULT</link>,  <link href=\"text/scalc/01/func_forecastetspimult.xhp\">FORECAST.ETS.PI.MULT</link>  <link href=\"text/scalc/01/func_forecastetsseason.xhp\">FORECAST.ETS.SEASONALITY</link>,  <link href=\"text/scalc/01/04060185.xhp#forecast\">FORECAST</link>,  <link href=\"text/scalc/01/04060185.xhp#forecastlinear\">FORECAST.LINEAR</link>"
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                "<bookmark_value>FORECAST.ETS.PI.MULT function</bookmark_value>"
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                "<ahelp hid=\"HID_FUNC_FORECAST_ETS_PIM\">Calculates the prediction interval(s) for multiplicative forecast based on the historical data using ETS or EDS algorithms.</ahelp>. EDS is used when argument <emph>period_length</emph> is 0, otherwise ETS is used."
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