Save cubic spline coefficients to use as response in regression
显示 更早的评论
Hi community,
I have two vectors and I would like to fit a cubic spline to:
y=[18.93000031 19.42000008 19.51000023 19.67000008 19.68000031 19.71999931];
x=[58.61111111 67.32055556 70.56194444 74.22694444 78.39388889 85.11555556];
I would also like to save the parameters of the fit at every point to use in regression analysis as my response (I want to change other variables at the points where I take a measurement in an experimental design.) How can I do this. I've not a very advanced matlab user but I hope this is an easier question for a pro in the community to answer.
3 个评论
John D'Errico
2015-2-24
(Despite my being reasonably knowledgable about splines and regression analysis) I have absolutely no idea what you mean by this statement:
"save the parameters of the fit at every point to use in regression analysis as my response"
Please clarify.
Ernest Modise - Kgamane
2021-3-2
Hi D'Errico,
Kindly assist,
Using your code example:
x=[58.61111111 67.32055556 70.56194444 74.22694444 78.39388889 85.11555556];
y=[18.93000031 19.42000008 19.51000023 19.67000008 19.68000031 19.71999931];
S = spline(x,y)
S =
form: 'pp'
breaks: [58.611 67.321 70.562 74.227 78.394 85.116]
coefs: [5x4 double]
pieces: 5
order: 4
dim: 1
I get the following error
>> splineeg
Error: File: splineeg.m Line: 4 Column: 5
Invalid expression. Check for missing or extra characters.
What could be the mistake,
采纳的回答
John D'Errico
2015-2-24
编辑：John D'Errico
2015-2-24
Ok. Why did you not say that? :)
x=[58.61111111 67.32055556 70.56194444 74.22694444 78.39388889 85.11555556];
y=[18.93000031 19.42000008 19.51000023 19.67000008 19.68000031 19.71999931];
S = spline(x,y)
S =
form: 'pp'
breaks: [58.611 67.321 70.562 74.227 78.394 85.116]
coefs: [5x4 double]
pieces: 5
order: 4
dim: 1
S.coefs
ans =
0.00053154 -0.013366 0.13235 18.93
0.00053154 0.00052218 0.020489 19.42
-0.0013274 0.005691 0.040628 19.51
0.00061302 -0.0089032 0.028855 19.67
0.00061302 -0.00124 -0.013411 19.68
Each row of S.coefs is the set of coefficients of one cubic polynomial segment. It can be evaluated by polyval, but be CAREFUL here. Those cubic polynomials are defined to be evaluated relative to the break point at the beginning of that interval.
So if I wanted to evaluate the first cubic segment at the point xhat = 59, I would do this:
xhat = 59;
polyval(S.coefs(1,:),xhat - S.breaks(1))
ans =
18.979
ppval(S,59)
ans =
18.979
As you can see, it yields the same prediction as ppval did. The reason for this offset is it makes the polynomial evaluation more stable with respect to numerical problems.
As part of my SLM toolbox (found on the File Exchange), I do provide a tool that allows you to extract the polynomials in a symbolic form.
polys = slmpar(S,'symabs')
polys =
[1x2 double] [1x2 double] [1x2 double] [1x2 double] [1x2 double]
[1x1 sym ] [1x1 sym ] [1x1 sym ] [1x1 sym ] [1x1 sym ]
So in symbolic form I removed the break point offset that was built into the polynomial, then return it as a symbolic "function" of x.
polys{2,1}
ans =
0.00053154425392522449377030735462313*x^3 - 0.1068293870770472518768171460159*x^2 + 7.1771491067641370730246290387668*x - 141.76724752093537873401498012911
And if I now substitute 59 into that polynomial, you also get the value you should expect.
subs(polys{2,1},59)
ans =
18.979480689855906097289602061928
I'm still not positive exactly what you intend as a goal, so if you need more help, please add further clarification. For example, my own SLM toolbox gives you a tool that does regression spline modeling.
3 个评论
John D'Errico
2015-2-24
Feel free to ask for more, as I am not certain what you will be doing with those cubic polynomial segments.
Are you trying now to use that spline itself in a regression? For example, if S(x) is the spline, are you trying to find calibration coefficients of some sort, so perhaps estimating the coefficients a and b below to fit some new set of data?
a + b*S(x)
Anthony Ortega
2017-3-18
ive been trying to get the coefficients from my cubic spline command thank you so much for this!
tzina kokkala
2018-2-15
May I ask, how can one plot the cubic spline S(x) from the beginning until the end point of x, when all that is available is x ,y and S.coefs?
更多回答（1 个）
Shoaibur Rahman
2015-2-24
pp = spline(x,y);
NewValue = [1 2]; % may be scaler or vector
out = ppval(pp,NewValue)
3 个评论
Brandon
2015-2-24
Shoaibur Rahman
2015-2-24
Perhaps, you have already got it! coefficients are in pp. NewValue is any value used for interpolation using the coefficients in pp. Thanks.
oshawcole
2017-9-29
How would you find a polynomial equation from the given x and y points?
类别
在 帮助中心 和 File Exchange 中查找有关 Spline Postprocessing 的更多信息
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!
Translated by 
