)f ( | )d f (y2 | , 2 )f ( | )d in VS .NET

Creating Data Matrix 2d barcode in VS .NET )f ( | )d f (y2 | , 2 )f ( | )d
)f ( | )d f (y2 | , 2 )f ( | )d
Decode Data Matrix In VS .NET
Using Barcode Control SDK for .NET Control to generate, create, read, scan barcode image in .NET framework applications.
f (y1 | , 2 )f (y2 | , 2 )f ( | )d f (y1 | , 2 )f ( | )d f (y2 | , 2 )f ( | )d
Printing DataMatrix In VS .NET
Using Barcode generator for .NET framework Control to generate, create ECC200 image in Visual Studio .NET applications.
Some extra notation is helpful:
DataMatrix Scanner In VS .NET
Using Barcode reader for .NET Control to read, scan read, scan image in VS .NET applications.
2 12 = 2 2 3 =
Bar Code Printer In VS .NET
Using Barcode creation for Visual Studio .NET Control to generate, create barcode image in .NET applications.
1 1 + nc ns
Read Bar Code In .NET
Using Barcode recognizer for Visual Studio .NET Control to read, scan read, scan image in VS .NET applications.
2 1 + 2 nc + ns
Data Matrix Drawer In Visual C#.NET
Using Barcode maker for VS .NET Control to generate, create Data Matrix ECC200 image in VS .NET applications.
ESTIMATION OF LIKELIHOOD RATIO
ECC200 Generation In VS .NET
Using Barcode encoder for ASP.NET Control to generate, create ECC200 image in ASP.NET applications.
nc y1 + ns y2 nc + ns
Generate Data Matrix In Visual Basic .NET
Using Barcode creator for .NET Control to generate, create Data Matrix 2d barcode image in .NET framework applications.
The value V of the evidence is given as V = 12 1 exp 1 (y1 y2 )2 2 2 12
Encoding European Article Number 13 In .NET
Using Barcode creator for VS .NET Control to generate, create EAN 13 image in Visual Studio .NET applications.
2 2 2(y1 + y2 w) + 3 2 + 2
Data Matrix 2d Barcode Maker In .NET
Using Barcode generator for VS .NET Control to generate, create Data Matrix 2d barcode image in .NET applications.
1 1 + nc ns
Print UPC-A Supplement 2 In VS .NET
Using Barcode generation for .NET framework Control to generate, create GTIN - 12 image in .NET applications.
(14.1)
Draw Postnet 3 Of 5 In .NET Framework
Using Barcode creation for .NET Control to generate, create Delivery Point Barcode (DPBC) image in VS .NET applications.
For estimations, the parameters and 2 are replaced by their estimates from the population data {xij , i = 1, . . . , m; j = 1, . . . , k}, namely (x) 1 and 2 sw , respectively. If the between-group distribution is assumed to be exponential, then an estimate of the value of evidence in a particular case with crime data y1 and suspect data y2 may be obtained with substitution of the appropriate numerical values for y1 and y2 in (14.1).
Code 39 Extended Reader In VS .NET
Using Barcode decoder for Visual Studio .NET Control to read, scan read, scan image in .NET framework applications.
14.2.2 Biweight Kernel Estimation
Code 3/9 Creation In Visual C#
Using Barcode printer for .NET framework Control to generate, create Code 3/9 image in Visual Studio .NET applications.
The use of a kernel density estimate based on the normal distribution is dif cult when there is an achievable lower bound to the range of the variable being modeled and the data are highly positively skewed so that much of the data are close to the lower bound. In the example to be discussed here, the lower bound is zero, and a kernel based on a normal distribution is very inaccurate close to this lower bound. A more appropriate approach for modeling a highly positively skewed distribution is the use of a biweight kernel [372] with a boundary kernel for use when the kernel comes close to the lower bound of the range of the random variable, in this case zero. The biweight kernel K(z) is de ned as K(z) = 15 (1 z2 )2 , 16 | z |< 1 (14.2)
Bar Code Printer In Java
Using Barcode drawer for Java Control to generate, create barcode image in Java applications.
This kernel is used to model the between-group distribution by way of the sample means {x1 , . . . , xm }. A general biweight kernel, with smoothing parameter h, and with a between-group variance of 2 , is given by 1 K h x h 15 = 16h 1 x h
Bar Code Creation In Visual Basic .NET
Using Barcode drawer for VS .NET Control to generate, create bar code image in .NET applications.
x h < < x + h . (14.3)
Bar Code Recognizer In Visual Studio .NET
Using Barcode scanner for VS .NET Control to read, scan read, scan image in .NET applications.
There are two candidates for the estimation of the between-group variance:
GS1-128 Generator In Visual Basic .NET
Using Barcode generation for VS .NET Control to generate, create EAN / UCC - 14 image in VS .NET applications.
2 1. sb = 2. 1/(x)2 m i=1 (x i 2 x . )2 /(m 1) sw /k
Painting EAN13 In Visual Studio .NET
Using Barcode drawer for ASP.NET Control to generate, create GS1 - 13 image in ASP.NET applications.
that is, the least-squares estimate and the method of moments estimate, respectively, of 2 , the between-group variance.
Encoding Code-128 In .NET
Using Barcode creation for ASP.NET Control to generate, create Code 128A image in ASP.NET applications.
APPLICATIONS V: FORENSIC GLASS ANALYSIS
The problem of a xed lower bound at zero is tackled with a boundary kernel. When an observation x is close to zero, a different kernel, known as the boundary kernel [372], is used. Closeness is de ned as x < h . For x > h , the biweight kernel (14.3) is used. For x < h , a boundary kernel Kh (z) = 2 1 z K(z) 2 0 2 1 (14.4)
is used, where K(z) is as given in (14.2). For ease of notation, denote h by . The terms 0 , 1 , and 2 are constants, functions of . For the kernel (14.2) these are de ned as t = zt K(z)dz, t = 0, 1, 2
where the dependency in on is suppressed. These constants can be shown to be 1 1 2 = 1 + 3 (35 42 2 + 15 4 ) 14 8 5 2 (3 3 2 + 4 ) 1 1 = 32 2 1 15 1 3 + 5 0 = + 2 16 3 5
2 In practice, the factor ( 2 1 z)/( 0 2 1 ) is close to 1. An optimal value of the smoothing parameter h is given by
hopt =
2/5
15 21
f (x)2 dx
1/5
m 1/5
[331]. Then it can be shown that, when f (x) = exp{ x}, hopt = which can be estimated by hopt = 70 m 70 m
1
x.
Likelihood Ratio with Biweight and Boundary Kernels
First, consider the denominator and the factor that is associated with the crime sample {y1i , i = 1, . . . , nc }. Denote this as Dc , which may be written as Dc = f (y11 , . . . , y1nc | , 2 )f ( | )d
The factor associated with the suspect sample may be derived analogously, so denote this as Ds . The rst term, Dc , in the denominator, with the biweight