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5GLs represent a more complete development environment with the objective that the code be automatically generated This way, code can be updated by modifying the 5GL statements, rather than by rewriting the entire code While it s interesting to review the evolution of software programming approaches, it is important to recognize that software has evolved not in a vacuum but right along with the computer hardware In fact, in the early days, large computer vendors gave away the system s software just as system and application software are now included in a bundle with personal computers As a result, in the early days of centralized computing, large organizations did their own programming and, although there were a few companies formed to provide custom software, by and large the idea of packaged software had not yet come about It would take the advent of the personal computer to change that paradigm.



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FREE Hindi OCR Software. WHAT IS OCR? Hindi OCR or Optical Character Recognition is a software or technique through which a scanned image of a Hindi​ ...

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Discriminant Analysis A limitation of ordinary linear models is the requirement that the dependent variable is continuous rather than discrete, but many interesting variables are categorical (discrete) patients may live or die, rms may go bankrupt or stay solvent, and so on Discriminant analysis is one of a range of techniques developed for analyzing data with categorical dependent variables The purpose of discriminant analysis is to predict membership in two or more mutually exclusive groups from a set of predictors Applied in this context, we want to predict whether rms will default over a speci ed period based on knowledge of their asset size, capital structure, EBITDA, and so on Discriminant analysis is not a regression model Rather, it is the inverse of a one-way multivariate analysis of variance (ANOVA).





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In addition, one of the most important developments for programming was the acceleration of the introduction of new computer systems Once new computers began coming out almost every year or two, existing computers and their associated software became obsolete Much of the work of programmers in the 1960s and 1970s was the continual rewriting of their programs to run on these new machines Even in the arena of large mainframe computers, however, some standardization began to emerge starting in the 1960s 3GL compilers improved the platform independence of programs written in languages such as Pascal or Fortran, although by no means were they universally transferable As the programming eld stabilized, however, software became recognized as an increasingly valuable corporate asset.

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That is, instead of minimizing the sum of squared errors, discriminant analysis maximizes the ratio of between group variance to within group variance (where the groups could be those that default and those that survive ) Mathematically, for two-category dependent variables (eg, default/no-default), ANOVA and discriminant analysis are the same The discriminant function is the linear combination of the independent variables that yields the largest mean differences between the groups If the discriminant score of the function is less than or equal to the cutoff score, the case is classed as 0; if it is above the cutoff score, it is classed as 1 To make this more concrete, let s look at a simple case We rst need to decide what time horizon to use for the default event Suppose we decide on a one-year time horizon.

Then, we need to use the values of the predictor variables (ie, nancial data) of each rm a year prior to the event of default Though it is less clear as to what time point to use for collecting the nancial data of nondefaulting rms, one might choose some sort of consistent scheme (for example, using averages of nancial data for the different one-year prior to default time points) Suppose our default model has just one predictor variable a nancial ratio and we want to estimate the relation between this variable and default, using a database of 40 defaults and 400 nondefaults In the regression, we set y = 1 for default and y = 0 for no default and we weight each default by the multiple of nondefaults to defaults (ie, 10) The resulting regression equation is shown in the following diagram..

This stability led to the emergence of computer science as an academic discipline at many universities in the late 1960s, but software engineering was yet to be adopted as a recognized eld of study When the number of computers began to rapidly expand in the 1960s, the demand for software grew accordingly This nally provided opportunities for.

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