Assigning exponential weights depending upon sample size

In summary, the individual is seeking help in finding a function that will assign exponential weights to a sequence of coefficients based on a given sample size. They mention adding each observation in the sequence to imply a weight of 1, resulting in a sum of weights equal to the sample size. They need these exponential weights to add up to the sample size in order to compare them to a uniformly weighted vector. The solution suggested is to pick m initial exponential weights, add them up, and then use the resulting sum to calculate the final weights. If this does not meet their needs, they are asked to clarify their definition of exponential weights.
  • #1
64jnk
4
0
I'm trying to find a function which will assign exponential weights depending upon sample size.

nu=an equally space coefficient sequence (.05,..,.5; by=.05).
m=sample size (10 in this case)

Adding each observation in nu, implies a weight of 1, which makes the sum of weights m.

I need to the exponential weights to add to m, given I'd like to compare the sum of this exponentially weighted vector to the sum of a uniformly weighted vector.

Would anyone be able to help with this please?

Many thanks,
 
Mathematics news on Phys.org
  • #2
64jnk said:
I need to the exponential weights to add to m

Pick m initial exponential weights a (whatever you mean by that), add them up. Let the sum be S. Then let the final weights be w = a (m / S).

If that doesn't suit you, try explaining what you mean by "exponential weights".
 
  • #3
I'm slightly embarrassed by how obvious this answer was. Thanks Stephen.
 

Related to Assigning exponential weights depending upon sample size

1. What is the purpose of assigning exponential weights depending upon sample size?

The purpose of assigning exponential weights is to give higher weight to larger sample sizes, as they are considered to be more reliable and representative of the population. This helps to reduce the impact of smaller, less reliable sample sizes on the overall analysis or conclusion.

2. How are exponential weights determined based on sample size?

The exponential weights are determined by using a mathematical formula, where the weight assigned to a sample is inversely proportional to its sample size. This means that larger sample sizes will have a smaller weight and smaller sample sizes will have a higher weight.

3. What are the advantages of using exponential weights in analysis?

Using exponential weights can help to improve the accuracy and precision of the analysis by reducing the impact of outliers or small sample sizes. It also allows for a more nuanced understanding of the data by giving more weight to larger sample sizes.

4. Are there any limitations to using exponential weights?

One limitation is that it assumes that larger sample sizes are always more reliable, which may not always be the case. Additionally, the choice of the exponent in the weight formula can also have an impact on the results, so it is important to carefully consider and justify this choice.

5. How can I determine the appropriate weight exponent to use?

The appropriate weight exponent can vary depending on the specific data and analysis being conducted. It is important to consider the goals and context of the analysis, as well as consulting with other experts in the field, to determine the most appropriate weight exponent for your particular study.

Similar threads

  • Set Theory, Logic, Probability, Statistics
Replies
1
Views
2K
Replies
9
Views
2K
  • Linear and Abstract Algebra
Replies
5
Views
1K
Replies
6
Views
4K
Replies
8
Views
2K
Replies
1
Views
1K
  • Introductory Physics Homework Help
Replies
9
Views
800
  • Introductory Physics Homework Help
Replies
11
Views
1K
  • Classical Physics
Replies
3
Views
347
  • Introductory Physics Homework Help
Replies
6
Views
1K
Back
Top