The below code is designed to generate data points placed equally spaced across a sine curve drawn in a specific interval. In the respective syntax, ‘n’refers to the polynomial power to that of the left-most coefficient in the polynomial ‘p’. Degree of polynomial fit: Degree of polynomial fit as inputs, are available being specified as any positive integer scalar.If y is the non-vector element, then this function polyfit() converts y into a column vector. The data points in x and their corresponding fitted function values contained in the vector y are formed. Fitted values at query points: Fitted values as inputs are available at query points being specified with the vector data type. If the vector x has recurring data points or if it needs centering and scaling, warning messages may result out. If x is non-vector element, then this function polyfit() converts x into a column vector.The data points in x and their corresponding fitted function values contained in the vector y are formed. Query Points: Query points are specified as an input of vector type.Using these two values, function polyfit()makes x centered at zero and scaledx to have a unit standard deviation, Mu(2) ) holds the value of standard of (x). Mu(1) holds a value of the mean of (x), and It results in a two-element vector having values-centered and scaled. It results in a structure S which can be used as input to the function polyval() in order to obtain error estimation. The coefficients in p are assigned to power in descending order and matching length of p to n+1. It generates the coefficients of the resultant polynomial p(x) with a degree of ‘n’, for the data set in yas the best fit in the view of a least-square.
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