Uniform linear splines is my equation correct?

In summary, the conversation discusses defining uniform linear splines, specifically the splines Hk:=H0(x−k), where H0={x, 0≤x<1, 2−x, 1≤x<2, 0, otherwise. The conversation also covers an incorrect calculation of H−1 and the correct version, H0(x+1)={x+1, 0≤x+1<1, 1−x, 1≤x+1<2. The participants clarify their understanding and come to a resolution.
  • #1
SMA_01
218
0
The question as stated: Define the uniform linear splines Hk:=H0(x−k), k=−1,0,1,2,3, where

H0={x, 0≤x<1,

2−x, 1≤x<2,

0, otherwise.

For k=−1, I would get:

H−1={x+1, 1≤x<2,

1−x, 2≤x<3,

0, otherwise.

Is that correct?

Thank you.
 
Last edited:
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  • #2
No. ##H_{-1}## would be ##H_0## translated one unit to the left. You moved it to the right.
 
  • #3
H−1(x)=H0(x+1), right?
H0(x)={x+1, 0≤x<1,
2−x, 1≤x<2,
0, otherwise}​
To get H0(x+1), wouldn't you write x+1 for x everywhere in the definition of H0(x)?
 
  • #4
LCKurtz-Wouldn't I just plug in k=-1, into H_0(x-(-1))=H_0(x+1)?
 
  • #5
haruspex-

I accidently put x+1 for the first function in H0, it's supposed to be x.

Yes, I see what you mean. I thought I did that though:
H−1={x+1, 1≤x<2,

1−x, 2≤x<3,

0, otherwise.

I don't see what I'm doing wrong...
 
  • #6
No, you should have got:
H0(x+1)={x+1, 0≤x+1<1,
1−x, 1≤x+1<2,​
 
  • #7
Oh okay, I see what you mean. I though I could evaluate it at the inequalities. Thanks!
 

FAQ: Uniform linear splines is my equation correct?

What are uniform linear splines?

Uniform linear splines are a type of mathematical function that is used to approximate a continuous and smooth curve. They are made up of connected line segments that intersect at specific points, known as knots. These knots are evenly spaced along the x-axis, giving the spline its "uniform" property.

How do I know if my equation is correct?

The best way to check if your equation for uniform linear splines is correct is to plot it on a graph and compare it to the original data. If the plotted points match or closely follow the data points, then your equation is likely correct. You can also double-check by plugging in different values for x and verifying that the output matches the corresponding y-values.

Can I use uniform linear splines for any type of data?

Uniform linear splines are best suited for data that exhibit a linear or near-linear relationship. This means that the data points should be fairly evenly spaced along the x-axis and follow a trend that can be approximated by straight line segments. If your data does not meet these criteria, another type of spline or function may be a better fit.

Are there any limitations to using uniform linear splines?

While uniform linear splines can be a useful tool for approximating data, they do have some limitations. For example, they may not be able to accurately capture sharp changes or discontinuities in the data. Additionally, the knots must be evenly spaced, which can be a disadvantage if your data is not evenly distributed.

How do I determine the number of knots to use in my equation?

The number of knots to use in your equation will depend on the complexity of your data and the desired level of accuracy. Generally, more knots will result in a more accurate approximation, but it is important to balance this with the complexity of the equation and the potential for overfitting. A good approach is to start with a small number of knots and gradually increase until the desired level of accuracy is achieved.

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