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However, how many times have you clicked past a dialog box that says the certificate is invalid, expired, or from an unknown source I work in security, but people still look at me funny when I ask if I m supposed to click past one of those to get to somewhere I need to go for work I m paranoid, so I always ask; but people with social skills get trained out of it really quickly We have all learned that it s okay if the certificate is bad Even if the certificate isn t bad, it still may be a fraud Several phishing websites have served their own certificates it means nothing, but it does put the https in the URL and the little padlock on the browser Or the scammer may actually go so far as to buy a real certificate They cost a few hundred dollars.

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criteria or log-likelihood functions The method converges under general conditions, but its rate of convergence may be insufficient This is improved by the Newton method discussed in Section 64 This is also a general function optimization method, but the conditions under which it converges are less general than those for the steepest descent method In Section 65, the Fisher scoring method is introduced Its iteration step is an approximation to the Newton step for maximizing log-likelihood functions of parameters of expectation models Therefore, the Fisher scoring method is a specialized method In Section 66, an expression is derived for the Newton step for maximizing the loglikelihood function for normally distributed observations Because of the particular form of the log-likelihood function concerned, this step is also the Newton step for minimizing the nonlinear least squares criterion for observations of any distribution.

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The one time I saw this (see Figure 5-1), the certificate lasted longer than the phishing site..

From the Newton step for normal observations, a much simpler approximate step may be derived The method using this step is called Gauss-Newton method and is the subject of Section 67 The Newton steps for maximizing the Poisson and the multinomial loglikelihood functions are discussed in Section 68 and Section 69, respectively In Section 610, an expression is derived for the Newton step for maximizing the log-likelihood function if the distribution of the observations is an exponential family From the Newton step for maximizing the log-likelihood function for exponential families of distributions, a much simpler approximate step may be derived that is used by the generalized Gauss-Newton method This method is the subject of Section 61 1 In Section 6.

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Click the Publish Options button to open the Publish Options dialog box, where you can specify how the DWF file will be published. You can do the following: Specify the location of the DWF file. Choose the type of DWF file single-sheet or multi-sheet. You would use a single-sheet format for people using an older viewer that doesn t support the multi-sheet format. Specify the DWF filename now, or ask to be prompted when you click the Publish button. Create a password. Include layer information. If you include layer information, the viewer can turn layers on or off. Include block information, including a template file for extracting attributes. (See 18 for more about block template files.) Include sheet set and sheet information if you are publishing a sheet set. In the view, lists files by their xref hierarchy and include materials.

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12, the iteratively reweighted least squares method is described and it is shown that it is identical to the generalized Gauss-Newton method and the Fisher scoring method if the distribution of the observations is a linear exponential family Like the Newton method, the Gauss-Newton method solves a system of linear equations for the step in each iteration The Levenberg-Marquardt method, discussed in Section 613, is a version of the Gauss-Newton method that can cope with (near-)singularity of these equations that could occur during the iteration process Section 614 is a summary of the numerical optimization methods discussed Finally, Section 615 is devoted to parameter estimation methodology A number of intermediate steps are recommended in the process starting with choosing a statistical model of the observations and ending with actually estimating the parameters from experimental observations..

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