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The rem has been defined since 1976 as equal to 0.01 sievert, which is the more commonly used SI unit outside the United States. Earlier definitions going back to 1945 were derived from the roentgen unit , which was named after Wilhelm Röntgen , a German scientist who discovered X-rays .
Polynomial curves fitting points generated with a sine function. The black dotted line is the "true" data, the red line is a first degree polynomial, the green line is second degree, the orange line is third degree and the blue line is fourth degree. The first degree polynomial equation = + is a line with slope a. A line will connect any two ...
Starting with initial values x 0 and x 1, we construct a line through the points (x 0, f(x 0)) and (x 1, f(x 1)), as shown in the picture above.In slope–intercept form, the equation of this line is
Figure 1. This Argand diagram represents the complex number lying on a plane.For each point on the plane, arg is the function which returns the angle . In mathematics (particularly in complex analysis), the argument of a complex number z, denoted arg(z), is the angle between the positive real axis and the line joining the origin and z, represented as a point in the complex plane, shown as in ...
Tangent line at (a, f(a)) In mathematics, a linear approximation is an approximation of a general function using a linear function (more precisely, an affine function). They are widely used in the method of finite differences to produce first order methods for solving or approximating solutions to equations.
A Lozenge diagram is a diagram that is used to describe different interpolation formulas that can be constructed for a given data set. A line starting on the left edge and tracing across the diagram to the right can be used to represent an interpolation formula if the following rules are followed: [5]
where ′ and ″ are the first and second derivatives of () with respect to . To make the spline take a shape that minimizes the bending (under the constraint of passing through all knots), we will define both y ′ {\displaystyle y'} and y ″ {\displaystyle y''} to be continuous everywhere, including at the knots.
Local regression or local polynomial regression, [1] also known as moving regression, [2] is a generalization of the moving average and polynomial regression. [3] Its most common methods, initially developed for scatterplot smoothing, are LOESS (locally estimated scatterplot smoothing) and LOWESS (locally weighted scatterplot smoothing), both pronounced / ˈ l oʊ ɛ s / LOH-ess.