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Study on formulas for calculation of empirical frequency in curve-fitting method

Huang Zhen

Open publisher page 1 citations

Abstract

A discussion is made on the theoretical basis of the curve fitting method and eleven formulas for calculation of the empirical frequency. By use of the statistical method, the design values by eight formulas are compared and analyzed for the curve fitting calculation of the population from the Pearson type III distribution. It is concluded that the calculated result by the Weiball formula is larger than its theoretical value, that the calculated results by the Huashi formula, the Haizen formula, and the Маматнов formula are satisfactory, and that the result by the least absolute value criterion is generally better than that by the least square criterion.

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What this paper is about

A discussion is made on the theoretical basis of the curve fitting method and eleven formulas for calculation of the empirical frequency. By use of the statistical method, the design values by eight formulas are compared and analyzed for the curve fitting calculation of the population from the Pearson type III distribution. It is concluded that the calculated result by the Weiball formula is larger than its theoretical value, that the calculated results by the Huashi formula, the Haizen formula, and the Маматнов formula are satisfactory, and that the result by the least absolute value criterion is generally better than that by the least square criterion.

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Available abstract

A discussion is made on the theoretical basis of the curve fitting method and eleven formulas for calculation of the empirical frequency. By use of the statistical method, the design values by eight formulas are compared and analyzed for the curve fitting calculation of the population from the Pearson type III distribution. It is concluded that the calculated result by the Weiball formula is larger than its theoretical value, that the calculated results by the Huashi formula, the Haizen formula, and the Маматнов formula are satisfactory, and that the result by the least absolute value criterion is generally better than that by the least square criterion.

Key concepts: Mathematics, Curve fitting, Statistics, Value (mathematics), Basis (linear algebra), Population, Applied mathematics, Mathematical analysis

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