Here is the R console output of factanal() We can look at the sums of squared (SS) loadings. Sum of squared loadings are the eigenvalues, or the variance in all variables which is accounted for by that factor (i.e., the eigenvalue/# of variables = proportion variance). If a factor has a “high” sum of squared loadings/eigenvalue, then it is helping to explain the variances. in the variables.

Quality Factor Calculator - Learning about Electronics A high quality factor indicates the bandpass is narrow. For example, let's assume that a bandpass filter circuit has a bandpass from 2KHz to 3KHz. Using the formula, we get Q-factor of 2.5. Since the bandpass filter is very narrow, the difference between f2 and f1 is small. Therefore, the denominator is relatively small, making for a large Q We present an algorithm for factoring integers of the form N = p r q for large r. Such integers were previously proposed for various cryptographic applications. When r ≈ log p our algorithm runs in Factoring N=p r q for large r Authors: D. Boneh, G. Durfee, and N. Howgrave-Graham. Abstract: We present an algorithm for factoring integers of the form N=p r q for large r. Such integers were previously proposed for various cryptographic applications. When r is close to log p our algorithm runs in polynomial time (in log N). Hence, we obtain a new class of integers that can be efficiently factored. N= prqs (where rand scan have the same size), is explicitly left as an open problem. To factor such None could let Q:= qsand try to apply BDH on N= prQ; however the condition for polynomial-time factorization becomes r’logQ’slogq; therefore this can only work if ris much larger than s. Alternatively a natural approach to factor N= prqs would be to

## Rt: Effective Reproduction Number

Factoring N prqs for Large r and s N= prqs (where rand scan have the same size), is explicitly left as an open problem. To factor such None could let Q:= qsand try to apply BDH on N= prQ; however the condition for polynomial-time factorization becomes r’logQ’slogq; therefore this can only work if ris much larger than s. Alternatively a natural approach to factor N= prqs would be to

### Nov 21, 2012

To create a factor in R, you use the factor() function. The first three arguments of factor() warrant some exploration: x: The input vector that you want to turn into a factor. levels: An optional vector of the values that x might have taken. The default is lexicographically sorted, unique values of x. labels: Another […] Quick-R: Factor Analysis Add the option scores="regression" or "Bartlett" to produce factor scores. Use the covmat= option to enter a correlation or covariance matrix directly. If entering a covariance matrix, include the option n.obs=. The factor.pa( ) function in the psych package offers a number of factor analysis related functions, including principal axis factoring. Recommended Home Insulation R– Values | ENERGY STAR