Claims Analysis
Total Claims: 13
Claim 1
Independent Claim
202 words
A method for analyzing a sample comprising the steps of: assembling a first plurality of known samples to provide a training set of known samples; sequentially placing each of the training set of known samples in a spectroscopic apparatus for measuring a property of the sample as a function of an observable parameter; measuring the property of the known samples to obtain a training set of spectra at a plurality of values of the observable parameters; storing said training set of spectra; forming a bootstrap distribution from the training set of spectra; measuring the property of test samples at the plurality of values of the observable parameters to obtain a set of test spectra; storing said test spectra; forming a univariate distribution from the bootstrap distribution, the univariate distribution comprising points of the bootstrap distribution located within a predetermined distance of a line between a center point of the bootstrap distribution and the test spectrum of the test sample; determining skew-adjusted confidence limits from the bootstrap distribution's center and a median of the training set median and a median of the univariate distribution; and determining whether the test sample is a member of the sample population based on the skew-adjusted confidence limits.
Claim 2
Independent Claim
202 words
A method for analyzing a sample comprising the steps of: assembling a first plurality of known samples to provide a training set of known samples; sequentially placing each of the training set of known samples in a spectroscopic apparatus for measuring a property of the sample as a function of an observable parameter; measuring the property of the known samples to obtain a training set of spectra at a plurality of values of the observable parameters; storing said training set of spectra; forming a bootstrap distribution from the training set of spectra; measuring the property of test samples at the plurality of values of the observable parameters to obtain a set of test spectra; storing said test spectra; forming a univariate distribution from the bootstrap distribution, the univariate distribution comprising points of the bootstrap distribution located within a predetermined distance of a line between a center point of the bootstrap distribution and the test spectrum of the test sample; determining skew-adjusted confidence limits from the bootstrap distribution's center and a median of the training set median and a median of the univariate distribution; and determining whether the test sample is a member of the sample population based on the skew-adjusted confidence limits.
Claim 3
Dependent Claim
37 words
The method of claim 1, wherein the points from the bootstrap distribution are located by forming a plurality of planes, each plane connecting the bootstrap distribution's center, a point in the bootstrap distribution, and the test spectrum.
Claim 4
Dependent Claim
45 words
The method of claim 1, wherein the skew-adjusted confidence limits are determined by calculating a projected difference between the bootstrap distribution's center and the training set's median projected onto the line, and adjusting the projected difference by a predetermined factor and the univariate distribution's median.
Claim 5
Dependent Claim
19 words
The method of claim 1, wherein the spectroscopic apparatus is a mass spectrometer, and the observable parameter is mass.
Claim 6
Dependent Claim
18 words
The method of claim 1, wherein the spectroscopic apparatus is a spectrometer, and the observable parameter is wavelength.
Claim 7
Dependent Claim
12 words
The method of claim 5, wherein the spectrometer is a near-infrared spectrometer.
Claim 8
Independent Claim
225 words
A method for testing a sample to determine if it is adulterated comprising the steps of: assembling a first plurality of known unadulterated samples to provide a training set of known unadulterated samples; sequentially placing each of the training set of known unadulterated samples in a spectroscopic apparatus for measuring a property of the sample as a function of an observable parameter; measuring the property of the known unadulterated samples to obtain a training set of spectra at a plurality of value of the observable parameters; storing said training set of spectra of known unadulterated samples; forming a bootstrap distribution from the training set of spectra; measuring the property of the test sample at the plurality of value of the observable parameters to obtain a set of test spectra; storing said test spectra; forming a univariate distribution from the bootstrap distribution, the univariate distribution comprising points of the bootstrap distribution located within a predetermined distance of a line between the center of the bootstrap distribution and the test spectra; determining skew-adjusted confidence limits by calculating a projected difference between the bootstrap distribution's center and a median of the training set projected onto the line, and adjusting the projected difference by a predetermined factor and a median of the univariate distribution; and determining whether the sample being tested is adulterated based on the skew-adjusted confidence limits.
Claim 9
Independent Claim
225 words
A method for testing a sample to determine if it is adulterated comprising the steps of: assembling a first plurality of known unadulterated samples to provide a training set of known unadulterated samples; sequentially placing each of the training set of known unadulterated samples in a spectroscopic apparatus for measuring a property of the sample as a function of an observable parameter; measuring the property of the known unadulterated samples to obtain a training set of spectra at a plurality of value of the observable parameters; storing said training set of spectra of known unadulterated samples; forming a bootstrap distribution from the training set of spectra; measuring the property of the test sample at the plurality of value of the observable parameters to obtain a set of test spectra; storing said test spectra; forming a univariate distribution from the bootstrap distribution, the univariate distribution comprising points of the bootstrap distribution located within a predetermined distance of a line between the center of the bootstrap distribution and the test spectra; determining skew-adjusted confidence limits by calculating a projected difference between the bootstrap distribution's center and a median of the training set projected onto the line, and adjusting the projected difference by a predetermined factor and a median of the univariate distribution; and determining whether the sample being tested is adulterated based on the skew-adjusted confidence limits.
Claim 10
Dependent Claim
38 words
The method of claim 7, wherein the points of the bootstrap distribution are located by forming a plurality of planes, each plane connecting the bootstrap distribution's center, a point in the bootstrap distribution, and the adulterated sample's spectrum.
Claim 11
Dependent Claim
19 words
The method of claim 7, wherein the spectroscopic apparatus is a mass spectrometer, and the observable parameter is mass.
Claim 12
Dependent Claim
18 words
The method of claim 7, wherein the spectroscopic apparatus is a spectrometer, and the observable parameter is wavelength.
Claim 13
Dependent Claim
12 words
The method of claim 10, wherein the spectrometer is a near-infrared spectrometer.