Monotone Piecewise Cubic Interpolation

By N. F., F. And, E. R., Carlson. 1980

Subfields: Numerical Methods & Scientific Computing

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Citations in the corpus

Approximating Spectral Densities of Large Matrices (2013, unknown): “oblem increases. Therefore, we can impose some constraints on the smoothness of the interpolating function in addition to monotonicity. One way to do this is to use the monotone splines introduced in [20, 21], and other choices of interpolating functions are also possible. The interpolation procedur”
Integral LOS Path Following for Curved Paths Based on a Monotone Cubic Hermite Spline Parametrization (2014, methodology): “Based on [35], we can interpolate the data between two waypoints ( x i , y i ) and ( x i + 1 , y i + 1 ) according to where with ( · ) denoting differentiation with respect to parameter θ , i = θ i + 1 − θ i is the local mesh spacing, and are the slopes of the piecewise linear interpolants.”
Labor Income Dynamics at Business-Cycle Frequencies:Implications for Portfolio Choice (2011, methodology): “Over the lower-end interval, the value function is approximated piecewise linearly or using the piecewise shape-preserving monotone cubic hermite interpolant of Fritsch and Carlson (1980).”
Copy Mean: A New Method to Impute Intermittent Missing Values in Longitudinal Studies (2013, methodology): “For mathematical details, see Fritsch and Carlson [13]. y”
Pulsar timing analysis in the presence of correlated noise (2011, methodology): “They are then interpolated onto a regular grid using a cubic spline constrained so its step response does not overshoot (Fritsch & Carlson 1980).”
Phase-sensitive specular neutron reflectometry for imaging the nanometer scale composition depth profile of thin-film materials (2012, methodology): “Freeform profiles and interfaces are based on monotone cubic splines [54].”
Interpolation among reduced‐order matrices to obtain parameterized models for design, optimization and probabilistic analysis (2009, methodology): “Spline interpolation among matrices as a function of the parameters z is performed with cubic splines [36, 37].”
kml and kml3d: R Packages to Cluster Longitudinal Data (2015, background): “For mathematical details, see Fritsch and Carlson (1980).”
Cubic-Spline Flows (2019, methodology): “ransforms Inspired by this direction of research, we introduce cubicspline ﬂows, a natural extension to the framework of Muller¨ et al. [20]. We propose to implement g i as a monotonic cubic spline [7], where each segment is deﬁned by a monotonically-increasing cubic polynomial (ﬁg. 1). Cubic splin”