Prediction of sunspot numbers
A. G. McNish, J. Virginia Lincoln
Abstract
A. G. McNish, J. Virginia Lincoln
Abstract
A formula for predicting smoothed annual sunspot numbers is developed. A first approximation to the prediction of a future value in a cycle is the mean of all past values for that part of the cycle. This estimate can be improved by adding to the mean a correction proportional to the departure of earlier values of the cycle from the mean cycle. These correction factors are determined by the method of least squares. Sunspot data for 1834 through 1943 are used, and statistical reasons for rejecting data of earlier years are presented. Reliability of the method is discussed on the basis of the standard deviations of predictions made for each of the years of the ten cycles in question, using all the prediction formulas developed. The prediction of three‐month means is also discussed.
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A formula for predicting smoothed annual sunspot numbers is developed. A first approximation to the prediction of a future value in a cycle is the mean of all past values for that part of the cycle. This estimate can be improved by adding to the mean a correction proportional to the departure of earlier values of the cycle from the mean cycle. These correction factors are determined by the method of least squares. Sunspot data for 1834 through 1943 are used, and statistical reasons for rejecting data of earlier years are presented. Reliability of the method is discussed on the basis of the standard deviations of predictions made for each of the years of the ten cycles in question, using all the prediction formulas developed. The prediction of three‐month means is also discussed.
Key concepts: Sunspot number, Standard deviation, Mathematics, Sunspot, Statistics, Reliability (semiconductor), Mean value, Applied mathematics