Question

我正在尝试在r中复制Matlabs csaps函数。我已经通过this问题成功实现了这一目标。

但是，在两种情况下，当我尝试更改权重时都会出现问题。在MATLAB中，权重是基于误差度量的，但是我不确定r的pspline函数中的w值对应什么，这会给我带来不同的结果

https://uk.mathworks.com/help/curvefit/csaps.html

这是一些示例代码： ----------------在MATLAB中------------------

% Run spline with weights = 1
Axis = 1:100;
Yval = sin((1:100)/20 *(2*pi));
weights = ones(size(Yval));
p = 0.0005;
pp = csaps(Axis, Yval, p, [], weights);
smoothed = fnval(pp, Axis)';

% Run spline with some select weights = 0
weights([5,8,10,15,17,19,24,...
        26,28,33,36,40,44,46,...
        49,50,55,60,64,68,74,...
        79,81,85,88,93,99,100])=0

pp2 = csaps(Axis, Yval, p, [], weights);
smoothed2 = fnval(pp2, Axis)';

plot(Axis,Yval)
hold on
plot(Axis,smoothed)
plot(Axis,smoothed2)

---------------- IN R ------------------

% Run spline with weights = 1
Axis  <- 1:100
Yval <-  sin((1:100)/20 *(2*pi))
weights <- rep(1,length(Yval))
p  <-  0.0005

pp <- pspline::smooth.Pspline(
  x = Axis, y =Yval, w = weights, spar = (1-p) / p )
smoothed <- c(predict(pp,Axis))

% Run spline with some select weights = 0
weights[c(5,8,10,15,17,19,24,
          26,28,33,36,40,44,46,
          49,50,55,60,64,68,74,
          79,81,85,88,93,99,100)] <- 0.00000000000000001

pp2 <- pspline::smooth.Pspline(
  x = Axis, y =Yval, w = weights, spar = (1-p) / p )
smoothed2 <- c(predict(pp2,Axis))
plot(Yval,t='l')
lines(smoothed,col = 2)
lines(smoothed2,col = 3)

R和Matlab中的结果是相同的（在四舍五入之内），没有加权，但是引入加权后，结果现在有所不同。两者都在后台运行FORTRAN样条函数。我无法弄清楚如何在R中运行pspline以获得这些权重相同的结果。

谢谢！

如何在pspline中添加权重:: smooth.Pspline R等同于MATLAB的csaps（）

0 个答案: