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I don’t understand what exactly has always been the difference between “in-sample” and therefore “out-of-sample” prediction?
The in-sample forecast uses a subset of the available statistics to predict values outside of the typical assessment period. Instead, this small sample forecast uses all the data you can get.
Are they correct?
In-Sample Prediction works by using a subset of personally available information to predict values outside of the evaluation period comparing them in the market with actual or known equivalent results. It involves evaluating the specific capabilities of the model versus what is expected versus what is known. Example one: The forecast example from May 2015 to 1980 uses dates from 1980 to 2012 to evaluate the model. Using the model, this near-future forecaster will forecast values for 2013-2015 and compare the predicted values with the finally known values.
Out-of-sample selection of forecast a. uses all available score sample numbers for Ms. a. The previous estimation example should be done between 1980 and 2015, and my predictions will start from 2016.
asked February 9, 2017 at 11:40 am.