How I do a Linear extrapolation?

Hi, I have a matrix with 160 numbers, but the first values is nan. How I complete this matrix? Anyone help me? I try the -- interp1 --- but I have only a matrix, I do not have a vector to realize the extrapolation.
Thank you for your attention. Best wishes, Paulo Oliveira

2 comentarios

José-Luis
José-Luis el 15 de Mayo de 2014
Extrapolation is tricky business. Depending on the sort of data different extrapolation methods might be warranted. The closest value? A linear interpolation from the first two points. A cuadratic function using the last three points? A spline of n degree?
Extrapolation caused the crash of the Challenger.
Paulo Oliveira
Paulo Oliveira el 15 de Mayo de 2014
I understand your questions, but as I said, I have 160 values, but 40 are NAN, so I have a 140 values to support,for you what the best way to do the data extrapolation?

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 Respuesta aceptada

Star Strider
Star Strider el 15 de Mayo de 2014
This works:
% Original vector:
x = 1:10
% Replace the first 4 elements with ‘NaN’:
x(1:4) = NaN
% Create empty elements for the ‘NaN’ elements:
x(isnan(x)) = []
% Extrapolate to fill the empty elements:
xm = interp1(x, -3:0, 'linear', 'extrap')
produces:
xm =
1. 2 3 4

4 comentarios

Paulo Oliveira
Paulo Oliveira el 15 de Mayo de 2014
Hi Star Strider,
I try with my matrix and works like I want. :)
Thank you for your attention.
Best wishes, Paulo Oliveira
Star Strider
Star Strider el 15 de Mayo de 2014
My pleasure!
Anwaar Alghamdi
Anwaar Alghamdi el 24 de Nov. de 2022
Editada: Anwaar Alghamdi el 24 de Nov. de 2022
@Star Strider Does this work if I have missing hourly temperature values? (not NaN but 999)
One or two missing values is fine but if a have a whole day missing? Can this preserve the behavior of hourly temprature profile within the day?
Star Strider
Star Strider el 29 de Abr. de 2023
@Anwaar Alghamdi — I just now saw this.
It depends on what the data are and where the values are that are NaN. The fillmissing function would likely be most appropriate.

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