Function B.Iso [addreg v3.0]

keywords

smooth

title

Defining Smooths in addreg.smooth Formulae

description

Function used in the definition of smooth terms within addreg.smooth model formulae. The function does not evaluate a smooth --- it exists purely to help set up a model using smooths.

Function tricubeMovingAverage [limma v3.28.14]

keywords

smooth

title

Moving Average Smoother With Tricube Weights

description

Apply a moving average smoother with tricube distance weights to a numeric vector.

Function wp.twin [AGD v0.39]

keywords

smooth

title

Superposes two worm plots

description

Superposes two worm plots from GAMLSS fitted objects. This is a diagnostic tool for comparing two solutions.

Function ffcsaps [dplR v1.6.9]

keywords

smooth

title

Smoothing Spline with User-Specified Rigidity and Frequency Cutoff

description

Applies a smoothing spline to y with rigidity determined by two parameters: frequency response f at a wavelength of nyrs years.

Function pass.filt [dplR v1.6.9]

keywords

smooth

title

Low-pass, high-pass, band-pass, and stop-pass filtering

description

Applies low-pass, high-pass, band-pass, or stop-pass filtering to y with frequencies (or periods) supplied by the user.

Function heavyPS [heavy v0.38.19]

keywords

smooth

title

Fit a penalized spline under heavy-tailed distributions

description

Fits a penalized spline to the supplied data.

Function neighborhood [prodlim v2018.04.18]

keywords

smooth

title

Nearest neighborhoods for kernel smoothing

description

Nearest neighborhoods for the values of a continuous predictor. The result is used for the conditional Kaplan-Meier estimator and other conditional product limit estimators.

Function awssigmc [dti v1.4]

keywords

smooth

title

Estimate noise variance for multicoil MR systems

description

The distribution of image intensity values \(S_i\) divided by the noise standard deviation in \(K\)-space \(\sigma\) in dMRI experiments is assumed to follow a non-central chi-distribution with \(2L\) degrees of freedom and noncentrality parameter \(\eta\), where \(L\) refers to the number of receiver coils in the system and \(\sigma \eta\) is the signal of interest. This is an idealization in the sense that each coil is assumed to have the same contribution at each location. For realistic modeling \(L\) should be a locally smooth function in voxel space that reflects the varying local influence of the receiver coils in the the reconstruction algorithm used. The functions assume \(L\) to be known and estimate either a local (function awslsigmc) or global ( function awssigmc) \(\sigma\) employing an assumption of local homogeneity for the noncentrality parameter \(\eta\). Function afsigmc implements estimates from Aja-Fernandez (2009). Function aflsigmc implements the estimate from Aja-Fernandez (2013).

Function smooth.demogdata [demography v1.22]

keywords

smooth

title

Create smooth demogdata functions

description

Smooth demogdata data using one of four methods depending on the value of method

Function cm.spline [demography v1.22]

keywords

smooth

title

Monotonic interpolating splines

description

Perform cubic spline monotonic interpolation of given data points, returning either a list of points obtained by the interpolation or a function performing the interpolation. The splines are constrained to be monotonically increasing (i.e., the slope is never negative).