Videoscribe version 2.3 is full of bug i prefer the previous version
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Whether this loss is potentially significant will depend on the metric being measured. Using either the EDF or a histogram, however, we do lose information regarding the order in which the values were observed. Summarizing measurements using histograms, on the other hand, in general loses information about the different values observed, so the EDF is preferred. Note that we can recover the different measured values and how many times each occurred from F(x) - no information regarding the range in values is lost.
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Sorts the data and returns the value that corresponds to the percentile as defined in RFC2330: Positive is peaked, negative is flattened. A value of zero is no skew, negative is a left skewed tail, positive is a right skewed tail. Calling the method without an argument returns the value of the flag. The flag is cleared whenever add_data is called. If you supply sorted data to the object, call this method to prevent the data from being sorted again. Since some of the methods in this class require sorted data, this saves some time. If called with a non-zero argument, this method sets a flag that says the data is already sorted and need not be sorted again.
#Videoscribe version 2.3 is full of bug i prefer the previous version update
Sort the stored data and update the mindex and maxdex methods. The smoothing method and coefficient need to be defined (see set_smoother), otherwise the function will return an undef value. Returns a copy of the smoothed data array. See Statistics::Smoother for more details. Set the method used to smooth the data and the smoothing coefficient. Note: Calling add_data with an empty array will delete all of your Full method cached values! Cached values for the sparse methods are not changed $stat->add_data_with_samples([) Cached values from Full methods are deleted since they are no longer valid. All of the sparse statistical values are updated and cached. $stat->add_data(1,2,4,5) Īdds data to the statistics variable. $stat = Statistics::Descriptive::Full->new() Ĭreate a new statistics object that inherits from Statistics::Descriptive::Sparse so that it contains all the methods described above. In some cases, several values can be cached at the same time. Similar to the Sparse Methods above, any Full Method that is called caches the current result so that it doesn't have to be recalculated. Returns the sample range (max - min) of the data set. Returns the index of the maximum value of the data set. Returns the maximum value of the data set. Returns the index of the minimum value of the data set.
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Returns the minimum value of the data set. Returns the standard deviation of the data. The cached statistical values are updated automatically. $stat->add_data(1,2,3) Īdds data to the statistics variable. $stat->clear() Įffectively the same as my $class = ref($stat) Įxcept more efficient. METHODS Sparse Methods $stat = Statistics::Descriptive::Sparse->new() Ĭreate a new sparse statistics object. Many of the methods (both Sparse and Full) cache values so that subsequent calls with the same arguments are faster. You may want to change this value to some small positive value such as 1e-24 in order to obtain error messages in case of very small denominators. Whenever a division by zero may occur, the denominator is checked to be greater than the value $Statistics::Descriptive::Tolerance, which defaults to 0.0. Using the full method, the entire data set is retained and additional functions are available. With the sparse method, none of the data is stored and only a few statistical measures are available. It has an object oriented design and supports two different types of data storage and calculation objects: sparse and full. This module provides basic functions used in descriptive statistics. $Statistics::Descriptive::Tolerance = 1e-10 DESCRIPTION My $stat = Statistics::Descriptive::Full->new() Version 3.0800 SYNOPSIS use Statistics::Descriptive Statistics::Descriptive - Module of basic descriptive statistical functions.