R smooth.spline (): suavizar spline no es suave pero sobreajusta mis datos

Question

May 30, 2016, 04:53 PM

spline smoothing regression curve-fitting r

R smooth.spline (): suavizar spline no es suave pero sobreajusta mis datos

Tengo varios puntos de datos que parecen adecuados para ajustar una spline a través de ellos. Cuando hago esto, obtengo un ajuste bastante irregular, como un sobreajuste, que no es lo que entiendo como suavizado.

¿Existe una opción / parámetro especial para recuperar la función de una spline realmente suave comoaquí.

El uso de lapenalty parámetro parasmooth.spline no tuvo ningún efecto visible. Tal vez lo hice mal?

Aquí hay datos y código:

results <- structure(
    list(
        beta = c(
            0.983790622281964, 0.645152464354322,
            0.924104713597375, 0.657703886566088, 0.788138034115623, 0.801080207252363,
            1, 0.858337365965949, 0.999687052533693, 0.666552625121279, 0.717453633245958,
            0.621570152961453, 0.964658181346544, 0.65071758770312, 0.788971505000918,
            0.980476054183113, 0.670263506919246, 0.600387040967624, 0.759173403408052,
            1, 0.986409675965, 0.982996471134736, 1, 0.995340781899163, 0.999855895958986,
            1, 0.846179233381267, 0.879226324448832, 0.795820998892035, 0.997586607285667,
            0.848036806290156, 0.905320944437968, 0.947709125535428, 0.592172373022407,
            0.826847031044922, 0.996916006944244, 0.785967729206612, 0.650346929853076,
            0.84206351833549, 0.999043126652724, 0.936879214753098, 0.76674066557003,
            0.591431233516217, 1, 0.999833445117791, 0.999606223666537, 0.6224971799303,
            1, 0.974537160571494, 0.966717133936379
        ), inventoryCost = c(
            1750702.95138889,
            442784.114583333, 1114717.44791667, 472669.357638889, 716895.920138889,
            735396.180555556, 3837320.74652778, 872873.4375, 2872414.93055556,
            481095.138888889, 538125.520833333, 392199.045138889, 1469500.95486111,
            459873.784722222, 656220.486111111, 1654143.83680556, 437511.458333333,
            393295.659722222, 630952.170138889, 4920958.85416667, 1723517.10069444,
            1633579.86111111, 4639909.89583333, 2167748.35069444, 3062420.65972222,
            5132702.34375, 838441.145833333, 937659.288194444, 697767.1875,
            2523016.31944444, 800903.819444444, 1054991.49305556, 1266970.92013889,
            369537.673611111, 764995.399305556, 2322879.6875, 656021.701388889,
            458403.038194444, 844133.420138889, 2430700, 1232256.68402778,
            695574.479166667, 351348.524305556, 3827440.71180556, 3687610.41666667,
            2950652.51736111, 404550.78125, 4749901.64930556, 1510481.59722222,
            1422708.07291667
        )
    ), .Names = c("beta", "inventoryCost"), class = c("data.frame")
)

plot(results$beta,results$inventoryCost)
mySpline <- smooth.spline(results$beta,results$inventoryCost, penalty=999999)
lines(mySpline$x, mySpline$y, col="red", lwd = 2)

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