How do we get the approximation?

In summary: Since we don't know $y(t^n)$ yet, we need to iterate to find it. (Thinking)We start with an initial estimate:$$y_n^{[0]} = y(t^{n-1})$$And then we can iterate with:$$y_{n}^{[i+1]} = y(t^{n-1}) + h f(t_{n}, y_{n}^{[i]})$$
  • #1
evinda
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Hello! (Wave)

Approximating $y'(t^n)$ at the relation $y'(t^n)=f(t^n,y(t^n))$ with the difference quotient $\left[\frac{y(t^{n+1})-y(t^n)}{h} \right]$ we get to the Euler method.

Approximating the same derivative with the quotient $\left[\frac{y(t^{n})-y(t^{n-1})}{h} \right]$ we get to the backward Euler method

$$y^{n+1}=y^n+hf(t^{n+1},y^{n+1}), n=0, \dots, N-1$$

where $y^0:=y_0$.
In order to find the formula for the forward Euler method, we use the limit $\lim_{h \to 0} \frac{y(x_0+h)-y(x_0)}{h}$ for $x_0=t^n, h=t^{n+1}-t^n$.
In order to find the formula for the backward Euler method, could we pick $h=t^{n-1}-t^n$ although it is negative?Or how do we get otherwise to the approximation:$$y'(t^n) \approx \frac{y(t^n)-y(t^{n-1})}{h}$$

?
 
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  • #2
evinda said:
In order to find the formula for the backward Euler method, could we pick $h=t^{n-1}-t^n$ although it is negative?

Or how do we get otherwise to the approximation:

$$y'(t^n) \approx \frac{y(t^n)-y(t^{n-1})}{h}$$

?

Hi! (Wave)

We should still pick $h$ positive.
I previously explained to http://mathhelpboards.com/members/mathmari/ how to find that derivative in this thread. (Thinking)
 
  • #3
I like Serena said:
Hi! (Wave)

We should still pick $h$ positive.
I previously explained to http://mathhelpboards.com/members/mathmari/ how to find that derivative in this thread. (Thinking)

Could you explain it further to me? (Thinking)
 
  • #4
evinda said:
Or how do we get otherwise to the approximation:

$$y'(t^n) \approx \frac{y(t^n)-y(t^{n-1})}{h}$$

?

evinda said:
Could you explain it further to me? (Thinking)

Since we don't know $y(t^n)$ yet, we need to iterate to find it. (Thinking)

We start with an initial estimate:
$$y_n^{[0]} = y(t^{n-1})$$
And then we can iterate with:
$$y_{n}^{[i+1]} = y(t^{n-1}) + h f(t_{n}, y_{n}^{})$$
(Wasntme)
 

1. How is the approximation calculated?

The approximation is calculated using various mathematical methods and models that take into account factors such as data points, error margins, and statistical analysis.

2. What data is used to make the approximation?

The data used to make the approximation can vary depending on the specific problem being addressed. It may include experimental data, observational data, or data from previous studies.

3. How accurate is the approximation?

The accuracy of the approximation depends on the quality of the data and the methods used to calculate it. It may also be affected by factors such as human error and variability in the data.

4. Can the approximation be improved?

Yes, the approximation can be improved by using more precise data, refining the calculation methods, and reducing sources of error. It may also be improved by incorporating feedback and new information.

5. Are there limitations to the approximation?

Yes, there are limitations to the approximation, as it is an estimation and not an exact solution. It may also be limited by the data available and the assumptions made in the calculation process.

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