The function is differentiable at when there is a real number such that
Equivalently, the difference quotient has a finite limit, and
Treat make as a categorical predictor, converting it to a factor explicitly if necessary:
fit3 <- lm(log(price) ~ mpg + psngr + length + width + weight + factor(make), data = cars)
The models are nested. The first nested-model F-test compares fit2 with the intercept-only fit1. Adding the five quantitative predictors reduces the residual sum of squares from to , with
There is overwhelming evidence that these quantitative car properties jointly improve the model.
The second test compares fit3 with fit2. Adding make reduces the residual sum of squares further to , with
Thus manufacturer has a highly significant effect even after adjusting for the five quantitative properties, and fit3 is preferred among these nested models.
There are observations because the intercept-only model has residual degrees of freedom. The make term uses additional degrees of freedom. By the degrees of freedom of a factor predictor, a factor with represented levels contributes degrees of freedom when an intercept is present. Hence
unique manufacturers occur in the dataset.
The other quantitative columns are mpg, psngr, length, width, and weight, so use
fit2 <- lm(log(price) ~ mpg + psngr + length + width + weight, data = cars)
This is a normal linear model with an intercept and five slopes.
Use the R linear-model formula with only its implicit intercept:
fit1 <- lm(log(price) ~ 1, data = cars)
This models every log-price by one common mean plus an error term.
An accepting derivation in a right-linear grammar has the form
with one active variable until the final terminal production.
If no variable repeated on any accepting derivation, an accepting derivation could contain at most variable occurrences. Since the production set is finite, only finitely many such derivations and hence finitely many terminal words would exist. The hypothesis that is infinite therefore supplies an accepting derivation in which some variable occurs twice.
Split this derivation at the two occurrences:
where . The first segment makes an accessible variable of a regular grammar, the middle segment makes it a looping variable of a regular grammar, and the last makes it a terminable variable of a regular grammar. Thus has all three properties, proving the accessible looping terminable variable criterion.
In every derivation beginning at , the terminal prefix remains unchanged because no production has a terminal on its left-hand side. By the sentential-form result, each step rewrites the sole variable at the right and appends terminals immediately before its successor variable. Hence
forces for some . Removing the inert prefix from every sentential form in the derivation gives
We prove the claim by induction on the length of the grammar derivation from . At length zero the sentential form is , which has the required form.
Suppose the current sentential form is . Because is terminal, the only symbol to which a production can apply is . A production produces
again a terminal word followed by one variable. A production produces the terminal word . Once a completely terminal word is reached, no further production can apply. The induction proves the sentential form of a right-linear regular grammar: every reachable is either or .
A grammar is a right-linear regular grammar when every production has one of the forms
where and . Thus a production has at most one variable on its right-hand side, and that variable is at the right end.
Let the computed eigenpair residual be
Define the rank-one matrix
Then
so is an exact eigenpair of the perturbed matrix . Moreover,
which is the backward error of an approximate eigenpair.
Follow the simple eigenvalue branch from for . The first-order perturbation of a simple eigenvalue and part (b) give
Since the residual is at the machine precision scale, this proves
The displayed matrix is an upper bidiagonal matrix. For , the right eigenvector equation successively gives
We may therefore take the unit right eigenvector to be .
For a left eigenvector, gives
Since ,
Choosing the initial scale produces
After normalization,
The eigenvalue sensitivity is therefore
where is the factorial. Hence
If is a real symmetric matrix, the finite-dimensional spectral theorem lets us choose the normalized left eigenvector and right eigenvector to be the same vector. Thus
More generally, the unitary diagonalization of a normal matrix shows that a real normal matrix also has coincident normalized left and right eigenspaces for each real eigenvalue. Since the question assumes , one can again choose , and every such simple eigenvalue has
Differentiate the eigenvalue equation
at , where . Suppressing the argument gives
Left-multiplication by the transpose of the unit left eigenvector and use of cancel the terms involving :
Because the eigenvalue is simple, , and hence the first-order perturbation of a simple eigenvalue is
The definition of the operator norm, followed by the Cauchy-Schwarz inequality, gives
Therefore
For a nonzero real vector , the Rayleigh quotient of the matrix is
The Rayleigh quotient iteration starts from a unit vector . Given , compute the shift
solve the linear system
and normalize in the Euclidean norm:
The next eigenvalue estimate is . The process stops when the eigenpair residual is sufficiently small.
Over , subtraction equals addition. The polynomial has the factorization
The two cubic factors have no root in , so they are irreducible, and they are reciprocal to one another. Put
Every cyclic code corresponds to one monic divisor of . The complete list is
Thus the two cubic generators give the two cyclic coordinate orientations of Hamming's code. Their duals have generators and and are the simplex codes. The remaining four are the familiar whole-space, even-weight, repetition, and zero codes. This is the complete classification of binary cyclic codes of length seven.
For the standard dot product on , the dual code is
It is an intersection of kernels of linear functions, and is therefore a linear code.
Let denote cyclic right shift. If and , then
A cyclic code is closed under both and , so and the right-hand side vanishes. Hence , proving directly that the dual of a cyclic code is cyclic.
Identify words with polynomials in . If the generator polynomial of a cyclic code is the monic divisor and
then the generator polynomial of is the monic reciprocal
Equivalently, the parity-check polynomial of one code becomes, after reversal, the generator polynomial of its dual.
The Taylor series of the shock density ratio at is
For a reversible adiabatic process, , so the density ratio predicted by the ideal-gas adiabat is
Equations (1) and (2) agree through order . Thus a weak shock satisfies the adiabatic pressure-density relation with an error of order , which in particular establishes the requested accuracy through .
Work in the shock frame, and let the positive upstream and downstream speeds be and . The Rankine-Hugoniot conditions for a perfect gas give conservation of mass and momentum:
Put
Mass conservation gives , and momentum conservation then gives
Applying the energy integral from part (a) on the two sides gives
Substitution of (1) into (2), followed by cancellation of , yields
Solving this linear equation for the density ratio gives
The one-dimensional mass flux and momentum flux are respectively
In a steady flow, the conservation laws make both the mass flux and the given energy flux
constant. Wherever , their ratio is therefore constant:
where is the internal energy per unit volume of the ideal gas. This is the required steady-flow energy integral.

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