uberpool estimate

Address: http://www.uml.org.cn/SoftWareProcess/201108264.asp What is agile poker? In fact, it should be called "estimation poker". In essence, it is a playing card. Based on the Delphi estimation principle, you can quickly estimate the number you need. About the number on playing cards Estimate the numbers on a playing card. Some cards are arranged by natural numbers, some are Fibonacci numbers, and some a

Maximum expectation algorithm: EM algorithm.In statistical calculation, the maximal expectation algorithm (EM) is an algorithm for finding the maximum likelihood estimation or the maximum posterior estimation in the probabilistic model, in which the probabilistic model relies on the invisible hidden variables.The maximum expectation algorithm is calculated by alternating two steps:The first step is to calculate the expectation (E), using the existing estimates of the hidden variables to calculat

DemandSuppose you want to design a function called estimate (), estimating the time it takes to write code for a specified number of lines, and expect that function to be available to different programmers. A portion of the code in Estimate () is the same for all users, but the function allows each programmer to provide its own algorithm to estimate time. To ac

is to design and evaluate the plan, from the perspective of risk management, review and comment on the Project Plan or plan, constantly look for any unexpected situations, and try to point out the management policies and common management methods for each risk, to handle the risks at any time, it is best for the risk manager to be held by persons other than the project supervisor. 4. Risk Identification Risk identification is an attempt to use a systematic method to identify known and predictab

TopicModel-PLSA model and EM derivation of PLSA The PLSA model based on probability statistics uses the EM algorithm to learn model parameters. The probability graph model of PLSA is as follows: D indicates the document, Z indicates the implied category or topic, W indicates the observed word, indicating the probability that the word appears in the document, and the probability that the word appears under the topic in the document, specifies the probability that a topic appears a word. Each top

MAP: Maximum posteriori probability (Maximum a posteriori)The estimation method obtains the point estimation of the hard-to-observe quantity based on empirical data. It is closely related to the Fisher method in maximum likelihood estimation,But it uses an enlarged optimization target, which fuses the prior distributions of the estimators. Therefore, the maximum posteriori estimate can be regarded as the maximum likelihood estimation of the regulariza

Why is the denominator of sample variance (sample variance) n-1?(Estimator, the variance of the main question is usually evaluated by the moments method.) If you are using an ML method, please do not think more than you think, the variance of the expectations of the estimator of the same is bias, interested in the same school can use their own positive state distribution calculation. ）Ben, by definition, the estimator of variance should be this:However, this estimator has bias because:and (n-1)/

a minute to do the time unit). Assuming that you are not 100% convinced of your experience, there may be a few degrees up or down deviations. We consider these deviations to be Gaussian white noise (Gaussian Noise), which means that the time is not related to these deviations and is in accordance with the Gaussian distribution (Gaussian distribution). In addition, we put a thermometer in the room, but the thermometer is not accurate, the measured value will be more than the actual value deviati

I'm going to deal with such an XML now Extra Long Standby "Battery life:" "charge estimate:" "Battery life" "charge estimate" Unknown Battery Details Android System WLA

how to transfer parameters to a script: ######################################## ############################ Analyze_table.sh ######### ######################################## ######################! /Bin/ksh # input parameter: 1: password #2: SID if ($ # To input parameters to execute the script, enter: $ Analyze_table.sh manager oradb1 The first part of the script generates an analyze. SQL file, which contains the statements used in the analysis table. The second part of the script analyze

http://blog.csdn.net/pipisorry/article/details/42560877Based on the PLSA model of probability statistics, the EM algorithm is used to learn the model parameters.The probability map model of PLSA is as followswhere d represents the document, Z represents the implied category or topic, W is the observed word, indicates the probability of the word appearing in the document, the probability of the word appearing under the topic in the document, and the probability of the word appearing on the given

/2.0 # The initial value of guess is set to x/2.0 diff = guess ** 2-x # The function value is stored in the diff variable ctr = 1 while abs (diff)> epsilon and ctr When the Newton Iteration Method itself fails, the approximate values will be repeated. 3. Comparison of efficiency between the bipartite method and the Newton Iteration Method We can test the function to compare the efficiency of the two: # Compare the efficiency def CprSquare (): print ('(2, 0.01)') squareRootBi2 (2, 0.01) square

Tags: www class div utility best important find traditional creatSource: Statistics in SQL Server histogram for no coverage of predicate predictions and changes in the estimation strategy (SQL2012--GT;SQL2014--GT;SQL2016) The source of this article: http://www.cnblogs.com/wy123/p/6770258.html Statistics have written a few related articles, feeling or not enjoyable, about the statistics of the problem, recently stepped on the pit, the problem although not very common, but also more interesting.R

Statistical Inference (Statistical Inference) is to make a certain degree of reliability estimation and judgment on the total number of features based on the actual data of the sample. The basic content of statistical inference includes parameter estimation and hypothesis test. In summary, studying a random variable, inferring its quantity characteristics, and changing according to the pattern is part of the estimation theory, it is a theoretical test to determine whether the quantitative charac

Maximum Likelihood Estimation: What we have been using in college learning is actually awesome! What is the maximum likelihood estimation?Q: Given a group of observed data, there is another model with a parameter to be determined. How can we estimate this unknown parameter? Observed Data (x1, Y1)... (Xn, yn) the undetermined model parameter is θ, and the model is f (x; θ ). At this time, we can use the observation data to