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  2. Density estimation - Wikipedia

    en.wikipedia.org/wiki/Density_Estimation

    In some fields such as signal processing and econometrics it is also termed the Parzen–Rosenblatt window method, after Emanuel Parzen and Murray Rosenblatt, who are usually credited with independently creating it in its current form. [10] [11] One of the famous applications of kernel density estimation is in estimating the class-conditional ...

  3. Kernel density estimation - Wikipedia

    en.wikipedia.org/wiki/Kernel_density_estimation

    Kernel density estimation of 100 normally distributed random numbers using different smoothing bandwidths.. In statistics, kernel density estimation (KDE) is the application of kernel smoothing for probability density estimation, i.e., a non-parametric method to estimate the probability density function of a random variable based on kernels as weights.

  4. Density - Wikipedia

    en.wikipedia.org/wiki/Density

    Density is an intensive property in that increasing the amount of a substance does not increase its density; rather it increases its mass. Other conceptually comparable quantities or ratios include specific density, relative density (specific gravity), and specific weight.

  5. Current density - Wikipedia

    en.wikipedia.org/wiki/Current_density

    In electromagnetism, current density is the amount of charge per unit time that flows through a unit area of a chosen cross section. [1] The current density vector is defined as a vector whose magnitude is the electric current per cross-sectional area at a given point in space, its direction being that of the motion of the positive charges at this point.

  6. Quantum clustering - Wikipedia

    en.wikipedia.org/wiki/Quantum_clustering

    Quantum Clustering (QC) is a class of data-clustering algorithms that use conceptual and mathematical tools from quantum mechanics. QC belongs to the family of density-based clustering algorithms, where clusters are defined by regions of higher density of data points. QC was first developed by David Horn and Assaf Gottlieb in 2001. [1]

  7. Multivariate kernel density estimation - Wikipedia

    en.wikipedia.org/wiki/Multivariate_kernel...

    The goal of density estimation is to take a finite sample of data and to make inferences about the underlying probability density function everywhere, including where no data are observed. In kernel density estimation, the contribution of each data point is smoothed out from a single point into a region of space surrounding it.

  8. Density meter - Wikipedia

    en.wikipedia.org/wiki/Density_meter

    A density meter (densimeter) is a device which measures the density of an object or material. Density is usually abbreviated as either ρ {\displaystyle \rho } or D {\displaystyle D} . Typically, density either has the units of k g / m 3 {\displaystyle kg/m^{3}} or l b / f t 3 {\displaystyle lb/ft^{3}} .

  9. Relative density - Wikipedia

    en.wikipedia.org/wiki/Relative_density

    Since the density of dry air at 101.325 kPa at 20 °C is [10] 0.001205 g/cm 3 and that of water is 0.998203 g/cm 3 we see that the difference between true and apparent relative densities for a substance with relative density (20 °C/20 °C) of about 1.100 would be 0.000120. Where the relative density of the sample is close to that of water (for ...