maksimidennäköisyyden
Maksimidennäköisyyden, often translated as maximum likelihood estimation, is a fundamental method for estimating the parameters of a statistical model. The core idea is to find the parameter values that maximize the probability of observing the given data. In simpler terms, it asks: what are the most likely parameters that would have produced the data we have?
The process begins with a statistical model that describes how the data is generated, depending on one
To achieve this, one typically takes the logarithm of the likelihood function, known as the log-likelihood function.
Once the log-likelihood function is defined, calculus techniques are commonly used. This involves taking the derivative
Maximum likelihood estimation has several desirable properties, including consistency (as the sample size increases, the estimates