THE TIME-VARYING CORRELATION ESTIMATOR USING THE NATURAL CUBIC SPLINE VOLATILITY

2020 ◽  
Vol 62 (1) ◽  
pp. 79-95
Author(s):  
Jetsada Laipaporn ◽  
Phattrawan Tongkumchum
Keyword(s):  
Cubic Spline ◽  
Time Varying ◽  
Natural Cubic Spline

A Procedure for Comparing Groups of Time-Dependent Measurements

1979 ◽  
Vol 18 (02) ◽  
pp. 84-88 ◽  
Author(s):  
H. Prestele ◽  
W. Gaus ◽  
L. Horbach
Keyword(s):  
Spline Function ◽  
Computing Time ◽  
Smooth Curve ◽  
Cubic Spline ◽  
Repeated Measurements ◽  
Time Dependent ◽  
Longitudinal Methods ◽  
Time Points ◽  
Calculation Of Parameters ◽  
Natural Cubic Spline

A three stop procedure is proposed for the comparison of groups, where for each individual a process is investigated on the basis of repeated measurements (e.g. 3 up to about 15 time points).1. A natural cubic spline function is fitted to the time-dependent measurements of each individual. A cubic spline is a function which is composed of piecewise polynomials, continuous up to and including second derivatives; it has a minimal »curvature«, so that a »smooth« curve is generated.2. For each individual the value of a problem-oriented parameter is estimated from the spline function.3. The values of the problem-oriented parameter are evaluated with standard, not necessarily longitudinal methods for estimating and hypothesis testing.The proposed procedure requires neither an equal number of measurements for each individual, nor the same time points of measurement for all individuals, nor equal length of the time intervals. Splines can be fitted to very different patterns of curves. They can be used for a more exact calculation of parameters adequate to the problem concerned. The procedure necessitates the use of a computer; programs are available and do not demand excessive arithmetic precision and computing time.

Cubic Spline Interpolation Method for the Envelope Tracking of Middle and Low Frequency Voltage Flicker

2014 ◽  
Vol 960-961 ◽  
pp. 704-709 ◽  
Author(s):  
Xiu Fang Jia ◽  
Hai Qing An ◽  
Shao Guang Zhang
Keyword(s):  
Interpolation Method ◽  
Spline Interpolation ◽  
Low Frequency ◽  
Cubic Spline ◽  
Time Varying ◽  
Envelope Tracking ◽  
Low Frequencies ◽  
Cubic Spline Interpolation ◽  
Signal Simulation ◽  
Voltage Flicker

Flicker envelope tracking is the key of analyzing voltage flicker signal. A novel method, i.e., cubic spline interpolation method is applied in the detection of the voltage flicker envelope. The typical flicker signals, such as one or multi-frequencies and frequency time-varying flicker signal are selected and analyzed by this method. Simulation results indicate that this method is effective in the detection of the envelope of voltage flicker signal. Results of one or multi-frequencies flicker signal simulation show that, when flicker frequency is less than 15Hz , the error of this method is quite tiny. The detection precision of this method is higher, especially in the scope of low frequencies of flicker and this method makes up for the disadvantage of square demodulation. Furthermore, results of frequency time-varying flicker signal simulation show that, the occurrence and recover time of voltage flicker signal can be accurately detected by cubic spline interpolation method.

A COMPARISON OF SPLINES INTERPOLATIONS WITH STANDARD FINITE DIFFERENCE METHODS FOR ONE-DIMENSIONAL ADVECTION-DIFFUSION EQUATION

2008 ◽  
Vol 19 (08) ◽  
pp. 1291-1304 ◽  
Author(s):  
MONTRI THONGMOON ◽  
SUWON TANGMANEE ◽  
ROBERT MCKIBBIN
Keyword(s):  
Finite Difference Methods ◽  
Cubic Spline ◽  
One Dimensional ◽  
Advection Diffusion Equation ◽  
Advection Diffusion ◽  
Constant Coefficients ◽  
Difference Methods ◽  
The One ◽  
Natural Cubic Spline ◽  
And Diffusion

Four types of numerical methods namely: Natural Cubic Spline, Special A-D Cubic Spline, FTCS and Crank–Nicolson are applied to both advection and diffusion terms of the one-dimensional advection-diffusion equations with constant coefficients. The numerical results from two examples are tested with the known analytical solution. The errors are compared when using different Peclet numbers.

Natural Cubic Spline Model for Estimating Volatility

2018 ◽  
Vol 8 (4) ◽  
pp. 1085
Author(s):  
Farida ◽  
Nifatamah Makaje ◽  
Phattrawan Tongkumchum ◽  
Aniruth Phon-On ◽  
Jetsada Laipaporn
Keyword(s):  
Cubic Spline ◽  
Natural Cubic Spline

scholarly journals Notes on EEG Resampling by Natural Cubic Spline Interpolation

2002 ◽  
Vol 6 (4) ◽  
pp. 73-80 ◽  
Author(s):  
Marco Congedo ◽  
Cem Özen ◽  
Leslie Sherlin
Keyword(s):  
Spline Interpolation ◽  
Cubic Spline ◽  
Cubic Spline Interpolation ◽  
Natural Cubic Spline

Computational Straightening of Images of Curved Macromolecular Helices by Cubic Spline Interpolation Facilitates Structural Analysis By Fourier Methods

1985 ◽  
Vol 43 ◽  
pp. 738-739 ◽  
Author(s):  
Alasdair C. Steven ◽  
Robert Stall ◽  
Peter M. Steinert ◽  
Benes L. Trus
Keyword(s):  
Spline Interpolation ◽  
Cubic Spline ◽  
A Posteriori ◽  
Biological Specimen ◽  
Cubic Spline Interpolation ◽  
3 Dimensional ◽  
Density Maps ◽  
Curvilinear Coordinate ◽  
Diffraction Patterns ◽  
Natural Cubic Spline

Powerful methods based on Fourier analysis have been devised for deducing the helical symmetries of macromolecular filaments and reconstructing their 3-dimensional density maps from electron images of negatively stained specimens. However, their applicability is restricted by the requirement that the particles be precisely straight. Only a limited number of specimens are sufficiently rigid to meet this constraint. Filamentous particles that exhibit varying degrees of flexibility constitute a much wider class of specimens, but their curvature impairs the coherence of their diffraction patterns. A solution to this problem is afforded by computational a posteriori straightening, effected by interpolating the digitized images on to a curvilinear coordinate system defined by the curve described by the particle axis. Here, we describe an algorithm for this purpose based on natural cubic spline interpolation, and illustrate its operation with model data and as applied to a flexuous biological specimen.

scholarly journals Interpolation of natural cubic spline

1992 ◽  
Vol 15 (2) ◽  
pp. 229-234 ◽  
Author(s):  
Arun Kumar ◽  
L. K. Govil
Keyword(s):  
Cubic Spline ◽  
Cubic Splines ◽  
Quadratic Spline ◽  
Natural Cubic Spline

From the result in [1] it follows that there is a unique quadratic spline which bounds the same area as that of the function. The matching of the area for the cubic spline does not follow from the corresponding result proved in [2]. We obtain cubic splines which preserve the area of the function.

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