smoothed estimation - definizione. Che cos'è smoothed estimation
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Cosa (chi) è smoothed estimation - definizione

CONSTRUCTION OF AN ESTIMATE, BASED ON OBSERVED DATA, OF AN UNOBSERVABLE UNDERLYING PROBABILITY DENSITY FUNCTION
Density Estimation; Probability estimation; Probability density estimation
  • Estimated probability of ''p'' (diabetes=1 | glu)
  • Histogram and density function for a Gumbel distribution <ref>[https://www.waterlog.info/cumfreq.htm A calculator for probability distributions and density functions]</ref>
  • Demonstration of density estimation using [[Kernel density estimation]]: The true density is mixture of two Gaussians centered around 0 and 3, shown with solid blue curve. In each frame, 100 samples are generated from the distribution, shown in red. Centered on each sample, a Gaussian kernel is drawn in gray. Averaging the Gaussians yields the density estimate shown in the dashed black curve.
  • Estimated probability of ''p''(diabetes=1 &#124; glu)
  • Estimated density of ''p'' (glu &#124; diabetes=1) (red), ''p''&nbsp;(glu &#124; diabetes=0) (blue), and ''p''&nbsp;(glu) (black)

Minimum-distance estimation         
METHOD FOR FITTING A STATISTICAL MODEL TO DATA
Minimum distance estimation
Minimum-distance estimation (MDE) is a conceptual method for fitting a statistical model to data, usually the empirical distribution. Often-used estimators such as ordinary least squares can be thought of as special cases of minimum-distance estimation.
Smoothed analysis         
  • A typical picture does not resemble a random bitmap.
Smoothed complexity; Smoothed Analysis
In theoretical computer science, smoothed analysis is a way of measuring the complexity of an algorithm. Since its introduction in 2001, smoothed analysis has been used as a basis for considerable research, for problems ranging from mathematical programming, numerical analysis, machine learning, and data mining.
estimate         
  • The exact number of candies in this jar cannot be determined by looking at it, because most of the candies are not visible. The amount can be estimated by presuming that the portion of the jar that cannot be seen contains an amount equivalent to the amount contained in the same volume for the portion that can be seen.
PROCESS OF FINDING AN ESTIMATE, OR APPROXIMATION, WHICH IS A VALUE THAT IS USABLE FOR SOME PURPOSE EVEN IF INPUT DATA MAY BE INCOMPLETE, UNCERTAIN, OR UNSTABLE
Overestimate; Estimated; Estimating; Calculated guess; Estimate
(estimated)
Frequency: The word is one of the 1500 most common words in English.
1.
If you estimate a quantity or value, you make an approximate judgment or calculation of it.
Try to estimate how many steps it will take to get to a close object...
I estimate that the total cost for treatment will be $12,500...
He estimated the speed of the winds from the degree of damage...
Some analysts estimate its current popularity at around ten per cent...
VERB: V wh, V that, V n, V n at amount
estimated
There are an estimated 90,000 gangsters in the country.
ADJ: a ADJ amount
2.
An estimate is an approximate calculation of a quantity or value.
...the official estimate of the election result...
This figure is five times the original estimate...
N-COUNT: usu with supp, oft N of/for n
3.
An estimate is a judgment about a person or situation which you make based on the available evidence.
I hadn't been far wrong in my estimate of his grandson's capabilities.
N-COUNT: oft with poss, N of n
4.
An estimate from someone who you employ to do a job for you, such as a builder or a plumber, is a written statement of how much the job is likely to cost.
N-COUNT

Wikipedia

Density estimation

In statistics, probability density estimation or simply density estimation is the construction of an estimate, based on observed data, of an unobservable underlying probability density function. The unobservable density function is thought of as the density according to which a large population is distributed; the data are usually thought of as a random sample from that population.

A variety of approaches to density estimation are used, including Parzen windows and a range of data clustering techniques, including vector quantization. The most basic form of density estimation is a rescaled histogram.