The `mfd` class represents a set of multidimensional functional data with `basismfd` object. Functional data objects are constructed by specifying a set of basis functions and a set of coefficients defining a linear combination of these basis functions.
Constructor for `mfd` objects (same as Mfd(...) )
Arguments
- argval
A list of numeric vectors of argument values at which the `mfd` object is to be evaluated
- X
A numeric matrix corresponds to basis expansion coefficients if `method="coefs"` and discrete observations if `method="data"`.
- mdbs
a basismfd object
- method
determine the `X` matrix type as "coefs" and "data".
Active bindings
basisan object of the class `basismfd`.
coefsa matrix of the coefficients.
nobsnumber of the observation
Methods
Method new()
Constructor for `mfd` objects (same as Mfd(...) )
Usage
mfd$new(argval = NULL, X, mdbs, method = "data")Arguments
argvalA list of numeric vectors of argument values at which the `mfd` object is to be evaluated
XA numeric matrix corresponds to basis expansion coefficients if `method="coefs"` and discrete observations if `method="data"`.
mdbsa basismfd object
methoddetermine the `X` matrix type as "coefs" and "data".
Method eval()
Evaluation an `mfd` object in some arguments.
Method print()
Print method for `mfd` objects
Examples
require(fda)
bs1 <- create.fourier.basis(c(0,2*pi),5)
bs2 <- create.bspline.basis(c(0,1),7)
bs3 <- create.exponential.basis(c(0,2),3)
#1-D mfd :_____________________________
argval <- seq(0,2*pi,length.out=100)
nobs <- 10;
X <- outer(sin(argval),seq(0.5,1.5,length.out=nobs))
mdbs1 <- Basismfd(bs1)
mfd1 <- Mfd(X=X, mdbs = mdbs1)
inprod_mfd(mfd1,mfd1)
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8]
#> [1,] 0.7853971 0.9599298 1.134462 1.308995 1.483528 1.658060 1.832593 2.007126
#> [2,] 0.9599298 1.1732475 1.386565 1.599883 1.813201 2.026518 2.239836 2.453154
#> [3,] 1.1344624 1.3865652 1.638668 1.890771 2.142874 2.394976 2.647079 2.899182
#> [4,] 1.3089951 1.5998829 1.890771 2.181659 2.472546 2.763434 3.054322 3.345210
#> [5,] 1.4835278 1.8132007 2.142874 2.472546 2.802219 3.131892 3.461565 3.791238
#> [6,] 1.6580605 2.0265184 2.394976 2.763434 3.131892 3.500350 3.868808 4.237266
#> [7,] 1.8325932 2.2398361 2.647079 3.054322 3.461565 3.868808 4.276051 4.683294
#> [8,] 2.0071259 2.4531538 2.899182 3.345210 3.791238 4.237266 4.683294 5.129322
#> [9,] 2.1816585 2.6664716 3.151285 3.636098 4.120911 4.605724 5.090537 5.575350
#> [10,] 2.3561912 2.8797893 3.403387 3.926985 4.450583 4.974181 5.497780 6.021378
#> [,9] [,10]
#> [1,] 2.181659 2.356191
#> [2,] 2.666472 2.879789
#> [3,] 3.151285 3.403387
#> [4,] 3.636098 3.926985
#> [5,] 4.120911 4.450583
#> [6,] 4.605724 4.974181
#> [7,] 5.090537 5.497780
#> [8,] 5.575350 6.021378
#> [9,] 6.060163 6.544976
#> [10,] 6.544976 7.068574
norm_mfd(mfd1)
#> [1] 0.8862263 1.0831655 1.2801047 1.4770439 1.6739830 1.8709222 2.0678614
#> [8] 2.2648006 2.4617398 2.6586789
mfd0 <- 2.5*mfd1
mfd1-mfd0
#> A 1-Dimensional 'mfd' object:
#> nobs: 10
#> basis 1:
#> type: fourier
#> nbasis: 5
#> support: 0 6.283185
mfd1[1:3]
#> A 1-Dimensional 'mfd' object:
#> nobs: 3
#> basis 1:
#> type: fourier
#> nbasis: 5
#> support: 0 6.283185
mfd1$eval(argval)
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 9.749324e-18 6.697330e-17 -1.247353e-16 3.392640e-17 -1.465435e-16
#> [2,] 3.171196e-02 3.875906e-02 4.580616e-02 5.285327e-02 5.990037e-02
#> [3,] 6.329623e-02 7.736205e-02 9.142788e-02 1.054937e-01 1.195595e-01
#> [4,] 9.462562e-02 1.156535e-01 1.366815e-01 1.577094e-01 1.787373e-01
#> [5,] 1.255740e-01 1.534793e-01 1.813847e-01 2.092900e-01 2.371953e-01
#> [6,] 1.560167e-01 1.906871e-01 2.253575e-01 2.600279e-01 2.946983e-01
#> [7,] 1.858312e-01 2.271271e-01 2.684229e-01 3.097187e-01 3.510145e-01
#> [8,] 2.148975e-01 2.626524e-01 3.104074e-01 3.581624e-01 4.059174e-01
#> [9,] 2.430984e-01 2.971202e-01 3.511421e-01 4.051639e-01 4.591858e-01
#> [10,] 2.703204e-01 3.303916e-01 3.904628e-01 4.505340e-01 5.106052e-01
#> [11,] 2.964540e-01 3.623326e-01 4.282113e-01 4.940899e-01 5.599686e-01
#> [12,] 3.213938e-01 3.928147e-01 4.642355e-01 5.356563e-01 6.070772e-01
#> [13,] 3.450395e-01 4.217150e-01 4.983904e-01 5.750658e-01 6.517413e-01
#> [14,] 3.672959e-01 4.489172e-01 5.305385e-01 6.121598e-01 6.937811e-01
#> [15,] 3.880732e-01 4.743117e-01 5.605502e-01 6.467887e-01 7.330272e-01
#> [16,] 4.072880e-01 4.977964e-01 5.883049e-01 6.788133e-01 7.693217e-01
#> [17,] 4.248627e-01 5.192767e-01 6.136906e-01 7.081045e-01 8.025185e-01
#> [18,] 4.407267e-01 5.386659e-01 6.366052e-01 7.345445e-01 8.324837e-01
#> [19,] 4.548160e-01 5.558862e-01 6.569564e-01 7.580267e-01 8.590969e-01
#> [20,] 4.670739e-01 5.708681e-01 6.746623e-01 7.784566e-01 8.822508e-01
#> [21,] 4.774511e-01 5.835514e-01 6.896516e-01 7.957519e-01 9.018521e-01
#> [22,] 4.859058e-01 5.938848e-01 7.018639e-01 8.098430e-01 9.178220e-01
#> [23,] 4.924039e-01 6.018270e-01 7.112500e-01 8.206731e-01 9.300962e-01
#> [24,] 4.969192e-01 6.073457e-01 7.177722e-01 8.281987e-01 9.386252e-01
#> [25,] 4.994337e-01 6.104189e-01 7.214042e-01 8.323894e-01 9.433747e-01
#> [26,] 4.999371e-01 6.110342e-01 7.221313e-01 8.332284e-01 9.443256e-01
#> [27,] 4.984274e-01 6.091890e-01 7.199507e-01 8.307123e-01 9.414740e-01
#> [28,] 4.949107e-01 6.048909e-01 7.148710e-01 8.248512e-01 9.348314e-01
#> [29,] 4.894012e-01 5.981571e-01 7.069129e-01 8.156687e-01 9.244245e-01
#> [30,] 4.819211e-01 5.890147e-01 6.961082e-01 8.032018e-01 9.102954e-01
#> [31,] 4.725004e-01 5.775005e-01 6.825006e-01 7.875007e-01 8.925008e-01
#> [32,] 4.611771e-01 5.636610e-01 6.661448e-01 7.686286e-01 8.711124e-01
#> [33,] 4.479969e-01 5.475518e-01 6.471066e-01 7.466615e-01 8.462163e-01
#> [34,] 4.330127e-01 5.292377e-01 6.254628e-01 7.216878e-01 8.179129e-01
#> [35,] 4.162849e-01 5.087927e-01 6.013005e-01 6.938082e-01 7.863160e-01
#> [36,] 3.978809e-01 4.862989e-01 5.747169e-01 6.631349e-01 7.515528e-01
#> [37,] 3.778748e-01 4.618470e-01 5.458191e-01 6.297913e-01 7.137635e-01
#> [38,] 3.563471e-01 4.355353e-01 5.147236e-01 5.939118e-01 6.731001e-01
#> [39,] 3.333845e-01 4.074699e-01 4.815554e-01 5.556408e-01 6.297263e-01
#> [40,] 3.090795e-01 3.777638e-01 4.464482e-01 5.151325e-01 5.838168e-01
#> [41,] 2.835299e-01 3.465366e-01 4.095432e-01 4.725499e-01 5.355565e-01
#> [42,] 2.568387e-01 3.139140e-01 3.709892e-01 4.280645e-01 4.851398e-01
#> [43,] 2.291133e-01 2.800273e-01 3.309414e-01 3.818554e-01 4.327695e-01
#> [44,] 2.004653e-01 2.450131e-01 2.895609e-01 3.341088e-01 3.786566e-01
#> [45,] 1.710101e-01 2.090123e-01 2.470145e-01 2.850168e-01 3.230190e-01
#> [46,] 1.408663e-01 1.721699e-01 2.034735e-01 2.347771e-01 2.660807e-01
#> [47,] 1.101553e-01 1.346342e-01 1.591132e-01 1.835921e-01 2.080711e-01
#> [48,] 7.900070e-02 9.655641e-02 1.141121e-01 1.316678e-01 1.492235e-01
#> [49,] 4.752802e-02 5.808980e-02 6.865159e-02 7.921337e-02 8.977515e-02
#> [50,] 1.586397e-02 1.938929e-02 2.291462e-02 2.643994e-02 2.996527e-02
#> [51,] -1.586397e-02 -1.938929e-02 -2.291462e-02 -2.643994e-02 -2.996527e-02
#> [52,] -4.752802e-02 -5.808980e-02 -6.865159e-02 -7.921337e-02 -8.977515e-02
#> [53,] -7.900070e-02 -9.655641e-02 -1.141121e-01 -1.316678e-01 -1.492235e-01
#> [54,] -1.101553e-01 -1.346342e-01 -1.591132e-01 -1.835921e-01 -2.080711e-01
#> [55,] -1.408663e-01 -1.721699e-01 -2.034735e-01 -2.347771e-01 -2.660807e-01
#> [56,] -1.710101e-01 -2.090123e-01 -2.470145e-01 -2.850168e-01 -3.230190e-01
#> [57,] -2.004653e-01 -2.450131e-01 -2.895609e-01 -3.341088e-01 -3.786566e-01
#> [58,] -2.291133e-01 -2.800273e-01 -3.309414e-01 -3.818554e-01 -4.327695e-01
#> [59,] -2.568387e-01 -3.139140e-01 -3.709892e-01 -4.280645e-01 -4.851398e-01
#> [60,] -2.835299e-01 -3.465366e-01 -4.095432e-01 -4.725499e-01 -5.355565e-01
#> [61,] -3.090795e-01 -3.777638e-01 -4.464482e-01 -5.151325e-01 -5.838168e-01
#> [62,] -3.333845e-01 -4.074699e-01 -4.815554e-01 -5.556408e-01 -6.297263e-01
#> [63,] -3.563471e-01 -4.355353e-01 -5.147236e-01 -5.939118e-01 -6.731001e-01
#> [64,] -3.778748e-01 -4.618470e-01 -5.458191e-01 -6.297913e-01 -7.137635e-01
#> [65,] -3.978809e-01 -4.862989e-01 -5.747169e-01 -6.631349e-01 -7.515528e-01
#> [66,] -4.162849e-01 -5.087927e-01 -6.013005e-01 -6.938082e-01 -7.863160e-01
#> [67,] -4.330127e-01 -5.292377e-01 -6.254628e-01 -7.216878e-01 -8.179129e-01
#> [68,] -4.479969e-01 -5.475518e-01 -6.471066e-01 -7.466615e-01 -8.462163e-01
#> [69,] -4.611771e-01 -5.636610e-01 -6.661448e-01 -7.686286e-01 -8.711124e-01
#> [70,] -4.725004e-01 -5.775005e-01 -6.825006e-01 -7.875007e-01 -8.925008e-01
#> [71,] -4.819211e-01 -5.890147e-01 -6.961082e-01 -8.032018e-01 -9.102954e-01
#> [72,] -4.894012e-01 -5.981571e-01 -7.069129e-01 -8.156687e-01 -9.244245e-01
#> [73,] -4.949107e-01 -6.048909e-01 -7.148710e-01 -8.248512e-01 -9.348314e-01
#> [74,] -4.984274e-01 -6.091890e-01 -7.199507e-01 -8.307123e-01 -9.414740e-01
#> [75,] -4.999371e-01 -6.110342e-01 -7.221313e-01 -8.332284e-01 -9.443256e-01
#> [76,] -4.994337e-01 -6.104189e-01 -7.214042e-01 -8.323894e-01 -9.433747e-01
#> [77,] -4.969192e-01 -6.073457e-01 -7.177722e-01 -8.281987e-01 -9.386252e-01
#> [78,] -4.924039e-01 -6.018270e-01 -7.112500e-01 -8.206731e-01 -9.300962e-01
#> [79,] -4.859058e-01 -5.938848e-01 -7.018639e-01 -8.098430e-01 -9.178220e-01
#> [80,] -4.774511e-01 -5.835514e-01 -6.896516e-01 -7.957519e-01 -9.018521e-01
#> [81,] -4.670739e-01 -5.708681e-01 -6.746623e-01 -7.784566e-01 -8.822508e-01
#> [82,] -4.548160e-01 -5.558862e-01 -6.569564e-01 -7.580267e-01 -8.590969e-01
#> [83,] -4.407267e-01 -5.386659e-01 -6.366052e-01 -7.345445e-01 -8.324837e-01
#> [84,] -4.248627e-01 -5.192767e-01 -6.136906e-01 -7.081045e-01 -8.025185e-01
#> [85,] -4.072880e-01 -4.977964e-01 -5.883049e-01 -6.788133e-01 -7.693217e-01
#> [86,] -3.880732e-01 -4.743117e-01 -5.605502e-01 -6.467887e-01 -7.330272e-01
#> [87,] -3.672959e-01 -4.489172e-01 -5.305385e-01 -6.121598e-01 -6.937811e-01
#> [88,] -3.450395e-01 -4.217150e-01 -4.983904e-01 -5.750658e-01 -6.517413e-01
#> [89,] -3.213938e-01 -3.928147e-01 -4.642355e-01 -5.356563e-01 -6.070772e-01
#> [90,] -2.964540e-01 -3.623326e-01 -4.282113e-01 -4.940899e-01 -5.599686e-01
#> [91,] -2.703204e-01 -3.303916e-01 -3.904628e-01 -4.505340e-01 -5.106052e-01
#> [92,] -2.430984e-01 -2.971202e-01 -3.511421e-01 -4.051639e-01 -4.591858e-01
#> [93,] -2.148975e-01 -2.626524e-01 -3.104074e-01 -3.581624e-01 -4.059174e-01
#> [94,] -1.858312e-01 -2.271271e-01 -2.684229e-01 -3.097187e-01 -3.510145e-01
#> [95,] -1.560167e-01 -1.906871e-01 -2.253575e-01 -2.600279e-01 -2.946983e-01
#> [96,] -1.255740e-01 -1.534793e-01 -1.813847e-01 -2.092900e-01 -2.371953e-01
#> [97,] -9.462562e-02 -1.156535e-01 -1.366815e-01 -1.577094e-01 -1.787373e-01
#> [98,] -6.329623e-02 -7.736205e-02 -9.142788e-02 -1.054937e-01 -1.195595e-01
#> [99,] -3.171196e-02 -3.875906e-02 -4.580616e-02 -5.285327e-02 -5.990037e-02
#> [100,] -1.127154e-16 -8.270575e-17 -3.016287e-16 -1.701814e-16 -3.778657e-16
#> [,6] [,7] [,8] [,9] [,10]
#> [1,] -2.818609e-17 4.072306e-17 7.461948e-18 -7.489899e-17 1.776679e-18
#> [2,] 6.694747e-02 7.399457e-02 8.104168e-02 8.808878e-02 9.513588e-02
#> [3,] 1.336254e-01 1.476912e-01 1.617570e-01 1.758229e-01 1.898887e-01
#> [4,] 1.997652e-01 2.207931e-01 2.418210e-01 2.628490e-01 2.838769e-01
#> [5,] 2.651007e-01 2.930060e-01 3.209113e-01 3.488166e-01 3.767220e-01
#> [6,] 3.293686e-01 3.640390e-01 3.987094e-01 4.333798e-01 4.680502e-01
#> [7,] 3.923104e-01 4.336062e-01 4.749020e-01 5.161979e-01 5.574937e-01
#> [8,] 4.536724e-01 5.014274e-01 5.491824e-01 5.969374e-01 6.446924e-01
#> [9,] 5.132077e-01 5.672295e-01 6.212514e-01 6.752732e-01 7.292951e-01
#> [10,] 5.706764e-01 6.307476e-01 6.908188e-01 7.508900e-01 8.109612e-01
#> [11,] 6.258473e-01 6.917259e-01 7.576046e-01 8.234832e-01 8.893619e-01
#> [12,] 6.784980e-01 7.499189e-01 8.213397e-01 8.927606e-01 9.641814e-01
#> [13,] 7.284167e-01 8.050922e-01 8.817676e-01 9.584431e-01 1.035119e+00
#> [14,] 7.754024e-01 8.570237e-01 9.386450e-01 1.020266e+00 1.101888e+00
#> [15,] 8.192657e-01 9.055042e-01 9.917427e-01 1.077981e+00 1.164220e+00
#> [16,] 8.598302e-01 9.503386e-01 1.040847e+00 1.131355e+00 1.221864e+00
#> [17,] 8.969324e-01 9.913463e-01 1.085760e+00 1.180174e+00 1.274588e+00
#> [18,] 9.304230e-01 1.028362e+00 1.126302e+00 1.224241e+00 1.322180e+00
#> [19,] 9.601671e-01 1.061237e+00 1.162308e+00 1.263378e+00 1.364448e+00
#> [20,] 9.860450e-01 1.089839e+00 1.193633e+00 1.297428e+00 1.401222e+00
#> [21,] 1.007952e+00 1.114053e+00 1.220153e+00 1.326253e+00 1.432353e+00
#> [22,] 1.025801e+00 1.133780e+00 1.241759e+00 1.349738e+00 1.457717e+00
#> [23,] 1.039519e+00 1.148942e+00 1.258365e+00 1.367789e+00 1.477212e+00
#> [24,] 1.049052e+00 1.159478e+00 1.269905e+00 1.380331e+00 1.490758e+00
#> [25,] 1.054360e+00 1.165345e+00 1.276330e+00 1.387316e+00 1.498301e+00
#> [26,] 1.055423e+00 1.166520e+00 1.277617e+00 1.388714e+00 1.499811e+00
#> [27,] 1.052236e+00 1.162997e+00 1.273759e+00 1.384521e+00 1.495282e+00
#> [28,] 1.044812e+00 1.154792e+00 1.264772e+00 1.374752e+00 1.484732e+00
#> [29,] 1.033180e+00 1.141936e+00 1.250692e+00 1.359448e+00 1.468204e+00
#> [30,] 1.017389e+00 1.124483e+00 1.231576e+00 1.338670e+00 1.445763e+00
#> [31,] 9.975009e-01 1.102501e+00 1.207501e+00 1.312501e+00 1.417501e+00
#> [32,] 9.735962e-01 1.076080e+00 1.178564e+00 1.281048e+00 1.383531e+00
#> [33,] 9.457712e-01 1.045326e+00 1.144881e+00 1.244436e+00 1.343991e+00
#> [34,] 9.141379e-01 1.010363e+00 1.106588e+00 1.202813e+00 1.299038e+00
#> [35,] 8.788237e-01 9.713315e-01 1.063839e+00 1.156347e+00 1.248855e+00
#> [36,] 8.399708e-01 9.283888e-01 1.016807e+00 1.105225e+00 1.193643e+00
#> [37,] 7.977357e-01 8.817078e-01 9.656800e-01 1.049652e+00 1.133624e+00
#> [38,] 7.522883e-01 8.314765e-01 9.106648e-01 9.898530e-01 1.069041e+00
#> [39,] 7.038117e-01 7.778972e-01 8.519826e-01 9.260681e-01 1.000154e+00
#> [40,] 6.525012e-01 7.211855e-01 7.898698e-01 8.585541e-01 9.272385e-01
#> [41,] 5.985632e-01 6.615698e-01 7.245765e-01 7.875831e-01 8.505898e-01
#> [42,] 5.422150e-01 5.992903e-01 6.563656e-01 7.134408e-01 7.705161e-01
#> [43,] 4.836836e-01 5.345976e-01 5.855117e-01 6.364257e-01 6.873398e-01
#> [44,] 4.232045e-01 4.677523e-01 5.123001e-01 5.568480e-01 6.013958e-01
#> [45,] 3.610213e-01 3.990235e-01 4.370257e-01 4.750280e-01 5.130302e-01
#> [46,] 2.973844e-01 3.286880e-01 3.599916e-01 3.912952e-01 4.225988e-01
#> [47,] 2.325500e-01 2.570290e-01 2.815079e-01 3.059869e-01 3.304658e-01
#> [48,] 1.667793e-01 1.843350e-01 2.018907e-01 2.194464e-01 2.370021e-01
#> [49,] 1.003369e-01 1.108987e-01 1.214605e-01 1.320223e-01 1.425841e-01
#> [50,] 3.349060e-02 3.701592e-02 4.054125e-02 4.406657e-02 4.759190e-02
#> [51,] -3.349060e-02 -3.701592e-02 -4.054125e-02 -4.406657e-02 -4.759190e-02
#> [52,] -1.003369e-01 -1.108987e-01 -1.214605e-01 -1.320223e-01 -1.425841e-01
#> [53,] -1.667793e-01 -1.843350e-01 -2.018907e-01 -2.194464e-01 -2.370021e-01
#> [54,] -2.325500e-01 -2.570290e-01 -2.815079e-01 -3.059869e-01 -3.304658e-01
#> [55,] -2.973844e-01 -3.286880e-01 -3.599916e-01 -3.912952e-01 -4.225988e-01
#> [56,] -3.610213e-01 -3.990235e-01 -4.370257e-01 -4.750280e-01 -5.130302e-01
#> [57,] -4.232045e-01 -4.677523e-01 -5.123001e-01 -5.568480e-01 -6.013958e-01
#> [58,] -4.836836e-01 -5.345976e-01 -5.855117e-01 -6.364257e-01 -6.873398e-01
#> [59,] -5.422150e-01 -5.992903e-01 -6.563656e-01 -7.134408e-01 -7.705161e-01
#> [60,] -5.985632e-01 -6.615698e-01 -7.245765e-01 -7.875831e-01 -8.505898e-01
#> [61,] -6.525012e-01 -7.211855e-01 -7.898698e-01 -8.585541e-01 -9.272385e-01
#> [62,] -7.038117e-01 -7.778972e-01 -8.519826e-01 -9.260681e-01 -1.000154e+00
#> [63,] -7.522883e-01 -8.314765e-01 -9.106648e-01 -9.898530e-01 -1.069041e+00
#> [64,] -7.977357e-01 -8.817078e-01 -9.656800e-01 -1.049652e+00 -1.133624e+00
#> [65,] -8.399708e-01 -9.283888e-01 -1.016807e+00 -1.105225e+00 -1.193643e+00
#> [66,] -8.788237e-01 -9.713315e-01 -1.063839e+00 -1.156347e+00 -1.248855e+00
#> [67,] -9.141379e-01 -1.010363e+00 -1.106588e+00 -1.202813e+00 -1.299038e+00
#> [68,] -9.457712e-01 -1.045326e+00 -1.144881e+00 -1.244436e+00 -1.343991e+00
#> [69,] -9.735962e-01 -1.076080e+00 -1.178564e+00 -1.281048e+00 -1.383531e+00
#> [70,] -9.975009e-01 -1.102501e+00 -1.207501e+00 -1.312501e+00 -1.417501e+00
#> [71,] -1.017389e+00 -1.124483e+00 -1.231576e+00 -1.338670e+00 -1.445763e+00
#> [72,] -1.033180e+00 -1.141936e+00 -1.250692e+00 -1.359448e+00 -1.468204e+00
#> [73,] -1.044812e+00 -1.154792e+00 -1.264772e+00 -1.374752e+00 -1.484732e+00
#> [74,] -1.052236e+00 -1.162997e+00 -1.273759e+00 -1.384521e+00 -1.495282e+00
#> [75,] -1.055423e+00 -1.166520e+00 -1.277617e+00 -1.388714e+00 -1.499811e+00
#> [76,] -1.054360e+00 -1.165345e+00 -1.276330e+00 -1.387316e+00 -1.498301e+00
#> [77,] -1.049052e+00 -1.159478e+00 -1.269905e+00 -1.380331e+00 -1.490758e+00
#> [78,] -1.039519e+00 -1.148942e+00 -1.258365e+00 -1.367789e+00 -1.477212e+00
#> [79,] -1.025801e+00 -1.133780e+00 -1.241759e+00 -1.349738e+00 -1.457717e+00
#> [80,] -1.007952e+00 -1.114053e+00 -1.220153e+00 -1.326253e+00 -1.432353e+00
#> [81,] -9.860450e-01 -1.089839e+00 -1.193633e+00 -1.297428e+00 -1.401222e+00
#> [82,] -9.601671e-01 -1.061237e+00 -1.162308e+00 -1.263378e+00 -1.364448e+00
#> [83,] -9.304230e-01 -1.028362e+00 -1.126302e+00 -1.224241e+00 -1.322180e+00
#> [84,] -8.969324e-01 -9.913463e-01 -1.085760e+00 -1.180174e+00 -1.274588e+00
#> [85,] -8.598302e-01 -9.503386e-01 -1.040847e+00 -1.131355e+00 -1.221864e+00
#> [86,] -8.192657e-01 -9.055042e-01 -9.917427e-01 -1.077981e+00 -1.164220e+00
#> [87,] -7.754024e-01 -8.570237e-01 -9.386450e-01 -1.020266e+00 -1.101888e+00
#> [88,] -7.284167e-01 -8.050922e-01 -8.817676e-01 -9.584431e-01 -1.035119e+00
#> [89,] -6.784980e-01 -7.499189e-01 -8.213397e-01 -8.927606e-01 -9.641814e-01
#> [90,] -6.258473e-01 -6.917259e-01 -7.576046e-01 -8.234832e-01 -8.893619e-01
#> [91,] -5.706764e-01 -6.307476e-01 -6.908188e-01 -7.508900e-01 -8.109612e-01
#> [92,] -5.132077e-01 -5.672295e-01 -6.212514e-01 -6.752732e-01 -7.292951e-01
#> [93,] -4.536724e-01 -5.014274e-01 -5.491824e-01 -5.969374e-01 -6.446924e-01
#> [94,] -3.923104e-01 -4.336062e-01 -4.749020e-01 -5.161979e-01 -5.574937e-01
#> [95,] -3.293686e-01 -3.640390e-01 -3.987094e-01 -4.333798e-01 -4.680502e-01
#> [96,] -2.651007e-01 -2.930060e-01 -3.209113e-01 -3.488166e-01 -3.767220e-01
#> [97,] -1.997652e-01 -2.207931e-01 -2.418210e-01 -2.628490e-01 -2.838769e-01
#> [98,] -1.336254e-01 -1.476912e-01 -1.617570e-01 -1.758229e-01 -1.898887e-01
#> [99,] -6.694747e-02 -7.399457e-02 -8.104168e-02 -8.808878e-02 -9.513588e-02
#> [100,] -2.867226e-16 -2.450279e-16 -3.055033e-16 -4.150787e-16 -3.656174e-16
mfd1c <- Mfd(X=mfd1$coefs, mdbs = mdbs1, method = "coefs")
all.equal(c(mfd1$basis,mfd1$coefs,mfd1$nobs),c(mfd1c$basis,mfd1c$coefs,mfd1c$nobs))
#> [1] TRUE
length(mfd1)
#> [1] 10
mean(mfd1)
#> A 1-Dimensional 'mfd' object:
#> nobs: 1
#> basis 1:
#> type: fourier
#> nbasis: 5
#> support: 0 6.283185
plot(mfd1)
