Batch
Properties
Fills up an array with the statistics defined by this interface statistics0 = getCount() statistics1 = getAverage() statistics2 = getStandardDeviation() statistics3 = getStandardError() statistics4 = getHalfWidth() statistics5 = getConfidenceLevel() statistics6 = getMin() statistics7 = getMax() statistics8 = getSum() statistics9 = getVariance() statistics10 = getDeviationSumOfSquares() statistics11 = getLastValue() statistics12 = getKurtosis() statistics13 = getSkewness() statistics14 = getLag1Covariance() statistics15 = getLag1Correlation() statistics16 = getVonNeumannLag1TestStatistic() statistics17 = getNumberMissing()
Returns a copy of the batch means array. Zero index is the first batch mean
A confidence interval for the mean based on the confidence level
Gets the confidence level. The default is given by Statistic.DEFAULT_CONFIDENCE_LEVEL = 0.95, which is a 95% confidence level
The header string for the CVS representation
the size of the current batch
Returns a copy of the StatisticIfc that is tabulating the current batch
Gets the sum of squares of the deviations from the average This is the numerator in the classic sample variance formula
Gets the lag-1 generate correlation of the unweighted observations. Note: See Box, Jenkins, Reinsel, Time Series Analysis, 3rd edition, Prentice-Hall, pg 31
Gets the lag-1 generate covariance of the unweighted observations. Note: See Box, Jenkins, Reinsel, Time Series Analysis, 3rd edition, Prentice-Hall, pg 31
The maximum number of batches as determined by the max num batches multiple
The minimum number of observations per batch
The minimum number of batches required
The multiple of the minimum number of batches that determines the maximum number of batches e.g. if the min. number of batches is 20 and the max number batches multiple is 2, then we can have at most 40 batches
Counts the number of observations that were negative, strictly less than zero.
the number of batches
When a data point having the value of (Double.NaN, Double.POSITIVE_INFINITY, Double.NEGATIVE_INFINITY) are presented it is excluded from the summary statistics and the number of missing points is noted. This method reports the number of missing points that occurred during the collection
the number of times re-batching has occurred
Counts the number of observations that were positive, strictly greater than zero.
Returns the relative error: getStandardError() / getAverage()
Returns the relative width of the default confidence interval: 2.0 * getHalfWidth() / getAverage()
Gets the sample standard deviation of the observations. Simply the square root of variance
Gets the standard error of the observations. Simply the generate standard deviation divided by the square root of the number of observations
Fills the map with the values of the statistics. Key is statistic label and value is the value of the statistic. The keys are: "Count" "Average" "Standard Deviation" "Standard Error" "Half-width" "Confidence Level" "Lower Limit" "Upper Limit" "Minimum" "Maximum" "Sum" "Variance" "Deviation Sum of Squares" "Kurtosis" "Skewness" "Lag 1 Covariance" "Lag 1 Correlation" "Von Neumann Lag 1 Test Statistic" "Number of missing observations"
Gets the total number of observations observed
Gets the Von Neumann Lag 1 test statistic for checking the hypothesis that the data are uncorrelated Note: See Handbook of Simulation, Jerry Banks editor, McGraw-Hill, pg 253.
Returns the asymptotic p-value for the Von Nueumann Lag-1 Test Statistic:
Functions
A confidence interval for the mean based on the confidence level
Return a copy of the information as an instance of a statistic
Returns a copy of the BatchStatistic
Computes the right most meaningful digit according to (int)Math.floor(Math.log10(a*getStandardError())) See doi 10.1287.opre.1080.0529 by Song and Schmeiser
Takes the current batch means and batches them into the specified number of batches. This does not change the current batch means
Returns the relative width of the level of the confidence interval: 2.0 * getHalfWidth(level) / getAverage()
Returns a data class holding the statistical data with the confidence interval specified by the given level.
Returns a data class holding the statistical data with the confidence interval specified by the given level. The class is suitable for inserting into a database table.
Converts a statistic to a data frame with two columns. The first column holds the names of the statistics and the second column holds the values. The valueLabel can be used to provide a column name for the value columns. By default, it is "Value".