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How to add weightings in pspline:: smooth.Pspline R equivalent of MATLAB's csaps()

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0

I am trying to replicate Matlabs csaps function in r. I have successfully achieved this with this question.

However problems arise when I try to change the weightings in both cases. In MATLAB the weightings are based on the error measure however I am unsure what the w values correspond to in pspline function in r and it gives me a different result

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

Here is some example code:
----------------IN MATLAB------------------

% 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)

The results in R and Matlab are identical (within rounding) without weightings, but when weights are introduced the results now differ. Both are running FORTRAN spline functions under the hood. I cant work out how to run pspline in R to get the same results with these weightings.

Thanks in advance!

r matlab

share|improve this question

edited Apr 1 at 11:19

Dan Lighter

asked Mar 26 at 15:08

Dan LighterDan Lighter

111 bronze badge

• 
  
  
  

  
  5
  

  
  
  
  
  
  

  
  
  can you show us some code?
  
  – LuckyLikey
  Mar 26 at 15:12
  

  
  
  
  


• 
  
  
  

  
  3
  

  
  
  
  
  
  

  
  
  Welcome to SO! Please edit your question to give a minimal reproducible example.
  
  – jogo
  Mar 26 at 15:19
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Sorry for the delay, I have attached an example to run to show the difference. Thanks
  
  – Dan Lighter
  Apr 1 at 11:21
  

  
  
  
  

add a comment | 

0

I am trying to replicate Matlabs csaps function in r. I have successfully achieved this with this question.

However problems arise when I try to change the weightings in both cases. In MATLAB the weightings are based on the error measure however I am unsure what the w values correspond to in pspline function in r and it gives me a different result

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

Here is some example code:
----------------IN MATLAB------------------

% 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)

The results in R and Matlab are identical (within rounding) without weightings, but when weights are introduced the results now differ. Both are running FORTRAN spline functions under the hood. I cant work out how to run pspline in R to get the same results with these weightings.

Thanks in advance!

r matlab

share|improve this question

edited Apr 1 at 11:19

Dan Lighter

asked Mar 26 at 15:08

Dan LighterDan Lighter

111 bronze badge

• 
  
  
  

  
  5
  

  
  
  
  
  
  

  
  
  can you show us some code?
  
  – LuckyLikey
  Mar 26 at 15:12
  

  
  
  
  


• 
  
  
  

  
  3
  

  
  
  
  
  
  

  
  
  Welcome to SO! Please edit your question to give a minimal reproducible example.
  
  – jogo
  Mar 26 at 15:19
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Sorry for the delay, I have attached an example to run to show the difference. Thanks
  
  – Dan Lighter
  Apr 1 at 11:21
  

  
  
  
  

add a comment | 

I am trying to replicate Matlabs csaps function in r. I have successfully achieved this with this question.

However problems arise when I try to change the weightings in both cases. In MATLAB the weightings are based on the error measure however I am unsure what the w values correspond to in pspline function in r and it gives me a different result

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

Here is some example code:
----------------IN MATLAB------------------

% 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)

The results in R and Matlab are identical (within rounding) without weightings, but when weights are introduced the results now differ. Both are running FORTRAN spline functions under the hood. I cant work out how to run pspline in R to get the same results with these weightings.

Thanks in advance!

r matlab

share|improve this question

edited Apr 1 at 11:19

Dan Lighter

asked Mar 26 at 15:08

Dan LighterDan Lighter

111 bronze badge

% 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)

% 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)

share|improve this question

edited Apr 1 at 11:19

Dan Lighter

asked Mar 26 at 15:08

Dan LighterDan Lighter

111 bronze badge

share|improve this question

edited Apr 1 at 11:19

Dan Lighter

asked Mar 26 at 15:08

Dan LighterDan Lighter

111 bronze badge

asked Mar 26 at 15:08

Dan LighterDan Lighter

111 bronze badge

asked Mar 26 at 15:08

Dan LighterDan Lighter

111 bronze badge