i was wondering.
of all the data structures like list linked list,stack,queues,graph of bfs and dfs.
hashing,sorting,searching,arrays...heaps,
can anyone of them be solved using computational methods and statistic like
linear regression,quadratic regression,trapezoidal rule,simpson's rule..which is to improve accuracy of integral..
just wondering is it possible??
Your question highlights some gaps in your understanding in the statistics area. As phrased at the moment the answer is no it is not possible but perhaps you could be clearer.
The data structure just contain data and are mathematically approximately just vectors
i was wondering.
of all the data structures like list linked list,stack,queues,graph of bfs and dfs.
hashing,sorting,searching,arrays...heaps,
sorting is a specialised task and for a set problem you can probably beat the built behaviour.
A vector can be used with a statistical method and this is what makes matrices powerful.
It is a simple iterative process to implement approximate integration
i was wondering.
can anyone of them be solved using computational methods and statistic like
linear regression,quadratic regression,trapezoidal rule,simpson's rule..which is to improve accuracy of integral..
so what is confusing in your question is the use of the word solved any statistical method can be implemented but to solve a data structure does not make sense.
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