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https://w.atwiki.jp/clickeridle/pages/77.html
URL https //veprogames.github.io/universe-shrinker/ 作成者 cook1eegames プラットフォーム HTML + JavaScript オフライン進行 無 宇宙を縮小する放置ゲーム。 ゲームの流れ Shrinkers Rho Upgrades Universe Layers Heat Death Autobuyer ガイド コメント ゲームの流れ Matter CondenserとUpgradeを購入して宇宙をプランク長まで縮小する。 Shrinkers Matter Condenserαからλまでの11種類ある。 Matter CondenserやUpgradeを購入するためのRho-Particles (ρp)を算出する能力（Production）と 宇宙を縮める能力（Shrink Power）がある。 Productionは加算式に対し、Shrink Powerは乗算式。 例えばShrink Powerが2なら宇宙は毎秒半分の直径に、10なら1桁縮み、1e100なら100桁縮むことになる。 ただし、Shrink Powerは宇宙が持つ「Resistance」に応じて減少する。 Rho Upgrades アップグレード名 コスト 上限 効果 Rho Boost 1000 なし All Generators produce more Rho-Particles Rho-Particlesの入手量が増加 Shrink Boost 10000 なし All Generators Shrink faster Shrink Powerが増加 Shrinking Expertise 1e7 なし All Generators are stronger based on how far you shrunk the Universe 現在の宇宙のshrink進行度に応じてRho-Particlesの入手量が増加 Rho Synergy 1e10 5 All Generators are stronger based on total Generator Levels Generatorレベルの総数に応じてRho-Particlesの入手量が増加 Shrink Boost 1e15 10 All Generators Shrink stronger based on total Generator Levels Generatorレベルの総数に応じてShrink Powerが増加 Universe Layers プランクスケールまで宇宙を縮小する事で手に入るshrunken universe(XXXverse)を使うことでアップグレードができる。 アップグレード名 コスト 上限 効果 Rho Fortifications 1.9^n なし All Generators produce more Rho-Particles Rho-Particlesの入手量が増加 Shrinking and Emsmalling 1.6^n なし All Generators shrink stronger Shrink Powerが増加 More Power, more Rho 2^(2+3n) なし All Generators more Rho-Particles based on total Verse shrunk そのXXXverseの累計shrink回数に応じてRho-Particlesの入手量が増加 Going small with Power 2^(4+5n) 10 All Generators shrink faster based on shrunk Verse you have right now 未使用のshrunken XXXverseの個数に応じてshrink powerが増加 宇宙 大きさ Resistance Rho Frotification Shrinking and Emsmalling Universe 8.848e10 Ly 1 2倍 +1.0乗 Multiverse 1e278 Ly 2 2.25倍 +1.4乗 Megaverse 1e1960 Ly 25 2.5倍 +1.8乗 Gigaverse 1e7419 Ly 10000 2.75倍 +1.8乗 Teraverse 1.543e34849 Ly 2e9 2.75倍 +1.8乗 Petaverse 3.118e102,329 Ly 3e13 2.75倍 +1.8乗 Exaverse 1.005e184,220 Ly 5e16 2.75倍 +1.8乗 Zettaverse 6.945e264,846 Ly 1e22 2.75倍 +1.8乗 Yottaverse 4.778e410,404 Ly 4e26 2.75倍 +1.8乗 Omniverse 1.057e999,984 Ly 1e31 2.75倍 +1.8乗 Heat Death Omniverseを1024回以上Shrinkする事で可能になる。 全てのUniverseをリセットすることでTheta Energyを得られる。 Theta Energyを使用してアップグレードを買う事ができる。 これらのアップグレードは買うたびに値上がりするほか、買っていないアップグレードも値上がりするので注意。（Respecは可能） アップグレード名 コスト 上限 効果 Rho Fortification Fortification 1 なし All Generators produce more Rho-Particles Rho-Particlesの入手量が増加 Shrinking the Shrinking 1 なし All Generators Shrink stronger Shrink Powerが増加 Unified Maxing 1 1 Max all affects all tabs (except Heat Death) instead of the current selected Max Allの効果が全てのタブに及ぶ More Heat, more Theta! 10^n なし Gain more Theta Energy on Heat Death Theta Energyの入手量増加 MultiMultiverse Upgrade なし Shrink multiple Verses at once Shrunken Verseの入手量が2^n倍になる Passive Shrinking 100 Shrink Universes lower than you have selected at a reduced rate 選択していないverseもshrinkするようになる Univerce Upgrade Power 1e7 なし All Shrinking Upgrades of Universe Layers are stronger Shrink Powerが増加するUniverse Upgradesが強化される Retain Layering 1e10 1 Keep your highest Universe reached (don't go back to Universe) Heat Death時にOmniverseまで開放された状態ではじまる Autobuyer Theta Energyを消費してShrinkers、Rho Upgrades、Universe Upgradesの購入を自動化できる。 ガイド 初Universeまで Productionは同じコストなら上位の物の方が強い。 Shrink Powerはαがやや強いが、効果はぜんぶ乗算されるのでαを優先的に購入する必要は特にない。 Omniverseまで Universe LayerのアップグレードはShrinkを優先。 同じコストならGoing small with Powerの方が効果が大きい。 Layerが進んでShrinking and Emsmallingを10倍程度まで買ったら下位のverseに戻ってアップグレードを買い足そう。 ShrinkersとRho Upgradesはさして重要ではないが、馬鹿にできない影響はあるので思い出したら買っておこう。 Heat Death後 やはりShrinkが重要。 MultiMultiverse Upgradeは他のアップグレードを買った時の値段上昇量が大きいので、RespecしてMultiMultiverse Upgrade→Shrinking the Shrinking→その他の順番で買いなおすと記録が伸びる場合がある コメント 買ってないアプグレのコストが増加って完全にRestackじゃんｗ (2022-06-30 22 49 51) 今Exaverseだけどあまりにも進まなさ過ぎてOmniverseまで進める気がしない・・・ (2022-07-11 15 17 11) コメント
https://w.atwiki.jp/wiki5_hks/pages/42.html
推定値の分散共分散行列 NONMEM のアウトプット中に（$COV を指定したときに）出力されてくる "Covariance Matrix of Estimate"． 通常はあまり使い道はないのだが，時々必要になる．例えば，パラメータの推定誤差を考慮して，多変量正規分布を仮定したシミュレーションを行いたい場合．http //blog.goo.ne.jp/hkasai/e/c17591b1b36a68ce3f3d4c3abd7669da しかし，アウトプットファイルにおける分散共分散行列推定値も，これまた利用しにくい． そこで，INFN 機能を利用して，この情報を取り出してみる．NTH, NETA, NEPS の行に，それぞれ，THETA, ETA, EPS の数を適切に指定する． 結果は COV.TXT というファイルに出力される．数値の意味はアウトプットの該当欄と見比べてみればすぐにわかるだろうから，説明省略． SUBROUTINE [[INFN]](ICALL, THETA, DATREC, INDXS, NEWIND) C INCLUDE 'C \NMV\NM\NSIZES' COMMON /CM12/ COVM(LPAR3) INTEGER MODE INTEGER NTH, NETA, NEPS INTEGER NALL C C THE NEXT 3 LINES SHOULD BE EDITED FOR THE NUMBERS OF ETAs, C THETAs AND EPSIILONs IN YOUR PROBLEM C NTH = 3 NETA = 3 NEPS = 1 C NALL = NTH + NETA*(NETA+1)/2 + NEPS*(NEPS+1)/2 NALL = NALL * (NALL+1) / 2 C IF (ICALL.EQ.0) THEN OPEN(51, FILE = 'COV.TXT') ENDIF C IF (ICALL.EQ.3) THEN MODE = 0 CALL PASS(MODE) MODE = 1 20 CALL PASS(MODE) IF (MODE.EQ.0) GO TO 30 GO TO 20 30 CONTINUE WRITE(51,*) (COVM(I),I=1,NALL) ENDIF C RETURN END
https://w.atwiki.jp/gtav/pages/882.html
逃走車両 - FIB襲撃作戦（Getaway Vehicle - The Bureau Raid） 逃走車両 - FIB襲撃作戦（Getaway Vehicle - The Bureau Raid）概要 ミッション攻略 ゴールドメダル取得条件 余談 動画 概要 FIB襲撃作戦、消防隊員プラン限定準備ミッション。 逃走車両をみつけ、任意の場所に置く。 ミッション攻略 4人乗れれば、なんでもよい。車両を用意し、FIBビルから離れた場所に置き、レスターに電話する。 ゴールドメダル取得条件 ▲▲▲▲●●●● ■■■■■■■■ ▲▲▲▲●●●● ■■■■■■■■ ▲▲▲▲●●●● ■■■■■■■■ 余談 FIBから消防車で逃走したあと、逃走車輌に乗り替え、レスターの自宅向かうための車輌。FIB襲撃のため縫製工場を処分するので、工場ではなくレスターの自宅が目的地となるため、FIBビルからレスター自宅の間に置くとよい。 動画
https://w.atwiki.jp/ce00582/pages/1500.html
Private Sub Command1_Click() Dim byear As Single Dim age As Single Dim car As Single Dim mis(1985 To 2100, 15 To 64, 1 To 49) As Single Dim mos(1985 To 2100, 15 To 64, 1 To 49) As Single Dim m2by(1900 To 2100, 15 To 69) As Single Dim f2by(1900 To 2100, 15 To 69) As Single Dim mdeby(1900 To 2100, 0 To 99) As Single Dim fdeby(1900 To 2100, 0 To 99) As Single Dim alpha(15 To 69) As Single Dim beta(15 To 69) As Single Dim gamma(15 To 69) As Single Dim theta(15 To 64) As Single Dim zan(1985 To 2100, 15 To 64, 1 To 49) As Single Dim zant(1985 To 2100, 15 To 64, 1 To 49) As Single Dim mde(1985 To 2100, 0 To 99) As Single Dim fnew(1985 To 2100) As Single Dim z1 As Single Dim z2 As Single Dim z3 As Single Dim v As Single Open "c /nagoya/gdata/変形生命表.txt " For Input As #1 Do Until EOF(1) Input #1, a1, a2, a3, a4 byear = a1 age = a2 mdeby(byear, age) = a3 fdeby(byear, age) = a4 Loop Close #1 Open "c /nagoya/data/女子脱退力.txt " For Input As #2 Do Until EOF(2) Input #2, a1, a2, a3, a4 age = a1 gamma(age) = a2 alpha(age) = a3 beta(age) = a4 Loop Close #2 Open "c /nagoya/data/再加入率.txt " For Input As #3 Do Until EOF(3) Input #3, a1, a2, a3, a4 age = a1 theta(age) = a3 Loop Close #3 Open "c /nagoya/gdata/変形厚生年金被保険者.txt " For Input As #5 Do Until EOF(5) Input #5, a1, a2, a3, a4 byear = a1 age = a2 m2by(byear, age) = a3 f2by(byear, age) = a4 Loop Close #5 For byear = 1990 To 2034 age = 15 mis(byear, age, 1) = f2by(byear, age) For age = 16 To 64 z1 = (1 - gamma(age - 1)) * f2by(byear, age - 1) z2 = f2by(byear, age) - z1 If z2 0 Then z2 = 0 z3 = (1 - theta(age)) * z2 z4 = theta(age) * z2 mis(byear, age, 1) = z3 z5 = 0 For car = 1 To 49 z5 = z5 + mos(byear, age - 1, car) Next If z5 = 0 Then z5 = 1 v = z4 / z5 If v 1 Then v = 1 For car = 2 To 49 mis(byear, age, car) = (1 - gamma(age - 1)) * mis(byear, age - 1, car - 1) + v * mos(byear, age - 1, car - 1) Next For car = 1 To 49 mos(byear, age, car) = (gamma(age - 1) - alpha(age - 1) - beta(age)) * mis(byear, age - 1, car) + (1 - fdeby(byear, age) - v) * mos(byear, age - 1, car) Next Next z1 = 0 For car = 25 To 49 z1 = z1 + mis(byear, 64, car) + mos(byear, 64, car) Next fnew(byear) = z1 Next Open "c /nagoya/gdata/女子新規裁定者1.txt " For Output As #4 For byear = 1990 To 2100 Write #4, byear, fnew(byear) Next Close #4 End Sub
https://w.atwiki.jp/ce00582/pages/156.html
Private Sub Command1_Click() Dim byear As Single Dim age As Single Dim car As Single Dim mis(1985 To 2100, 15 To 64, 1 To 49) As Single Dim mos(1985 To 2100, 15 To 64, 1 To 49) As Single Dim m2by(1900 To 2100, 15 To 69) As Single Dim f2by(1900 To 2100, 15 To 69) As Single Dim mdeby(1900 To 2100, 0 To 99) As Single Dim fdeby(1900 To 2100, 0 To 99) As Single Dim alpha(15 To 69) As Single Dim beta(15 To 69) As Single Dim gamma(15 To 69) As Single Dim theta(15 To 64) As Single Dim zan(1985 To 2100, 15 To 64, 1 To 49) As Single Dim zant(1985 To 2100, 15 To 64, 1 To 49) As Single Dim mde(1985 To 2100, 0 To 99) As Single Dim fnew(1985 To 2100) As Single Dim z1 As Single Dim z2 As Single Dim z3 As Single Dim v As Single Open "c /stream/gdata/変形生命表.txt " For Input As #1 Do Until EOF(1) Input #1, a1, a2, a3, a4 byear = a1 age = a2 mdeby(byear, age) = a3 fdeby(byear, age) = a4 Loop Close #1 Open "c /stream/data/女子脱退力.txt " For Input As #2 Do Until EOF(2) Input #2, a1, a2, a3, a4 age = a1 gamma(age) = a2 alpha(age) = a3 beta(age) = a4 Loop Close #2 Open "c /stream/data/再加入率.txt " For Input As #3 Do Until EOF(3) Input #3, a1, a2, a3 age = a1 theta(age) = a3 Loop Close #3 Open "c /stream/gdata/変形厚生年金被保険者.txt " For Input As #5 Do Until EOF(5) Input #5, a1, a2, a3, a4 byear = a1 age = a2 m2by(byear, age) = a3 f2by(byear, age) = a4 Loop Close #5 For byear = 1985 To 2034 age = 15 mis(byear, age, 1) = f2by(byear, age) For age = 16 To 64 z1 = (1 - gamma(age - 1)) * f2by(byear, age - 1) z2 = m2by(byear, age) - z1 If z2 0 Then z2 = 0 z3 = (1 - theta(age)) * z2 z4 = theta(age) * z2 mis(byear, age, 1) = z3 z5 = 0 For car = 1 To 49 z5 = z5 + mos(byear, age - 1, car) Next If z5 = 0 Then z5 = 1 v = z4 / z5 If v 1 Then v = 1 For car = 2 To 49 mis(byear, age, car) = (1 - gamma(age - 1)) * mis(byear, age - 1, car - 1) + v * mos(byear, age - 1, car - 1) Next For car = 1 To 49 mos(byear, age, car) = (gamma(age - 1) - alpha(age - 1) - beta(age)) * mis(byear, age - 1, car) + (1 - mdeby(byear, age) - v) * mos(byear, age - 1, car) Next Next z1 = 0 For car = 25 To 49 z1 = z1 + mis(byear, 64, car) + mos(byear, 64, car) Next fnew(byear) = z1 Next Open "c /stream/gdata/女子新規裁定者1.txt " For Output As #4 For byear = 1985 To 2100 Write #4, byear, fnew(byear) Next Close #4 End Sub
https://w.atwiki.jp/ce00582/pages/1440.html
Private Sub Command1_Click() Dim byear As Single Dim age As Single Dim car As Single Dim mis(1985 To 2100, 15 To 64, 1 To 49) As Single Dim mos(1985 To 2100, 15 To 64, 1 To 49) As Single Dim m2by(1900 To 2100, 15 To 69) As Single Dim f2by(1900 To 2100, 15 To 69) As Single Dim mdeby(1900 To 2100, 0 To 99) As Single Dim fdeby(1900 To 2100, 0 To 99) As Single Dim alpha(15 To 69) As Single Dim beta(15 To 69) As Single Dim gamma(15 To 69) As Single Dim theta(15 To 64) As Single Dim zan(1985 To 2100, 15 To 64, 1 To 49) As Single Dim zant(1985 To 2100, 15 To 64, 1 To 49) As Single Dim mde(1985 To 2100, 0 To 99) As Single Dim mnew(1985 To 2100) As Single Dim z1 As Single Dim z2 As Single Dim z3 As Single Dim v As Single Open "c /kirakira/gdata/変形生命表.txt " For Input As #1 Do Until EOF(1) Input #1, a1, a2, a3, a4 byear = a1 age = a2 mdeby(byear, age) = a3 fdeby(byear, age) = a4 Loop Close #1 Open "c /kirakira/data/男子脱退率.txt " For Input As #2 Do Until EOF(2) Input #2, a1, a2, a3, a4 age = a1 gamma(age) = a2 alpha(age) = a3 beta(age) = a4 Loop Close #2 Open "c /kirakira/data/再加入率.txt " For Input As #3 Do Until EOF(3) Input #3, a1, a2, a3 age = a1 theta(age) = a2 Loop Close #3 Open "c /kirakira/gdata/変形厚生年金被保険者.txt " For Input As #5 Do Until EOF(5) Input #5, a1, a2, a3, a4 byear = a1 age = a2 m2by(byear, age) = a3 f2by(byear, age) = a4 Loop Close #5 For byear = 1985 To 2034 age = 15 mis(byear, age, 1) = m2by(byear, age) For age = 16 To 64 z1 = (1 - gamma(age - 1)) * m2by(byear, age - 1) z2 = m2by(byear, age) - z1 If z2 0 Then z2 = 0 z3 = (1 - theta(age)) * z2 z4 = theta(age) * z2 mis(byear, age, 1) = z3 z5 = 0 For car = 1 To 49 z5 = z5 + mos(byear, age - 1, car) Next If z5 = 0 Then z5 = 1 v = z4 / z5 If v 1 Then v = 1 For car = 2 To 49 mis(byear, age, car) = (1 - gamma(age - 1)) * mis(byear, age - 1, car - 1) + v * mos(byear, age - 1, car - 1) Next For car = 1 To 49 mos(byear, age, car) = (gamma(age - 1) - alpha(age - 1) - beta(age)) * mis(byear, age - 1, car) + (1 - mdeby(byear, age) - v) * mos(byear, age - 1, car) Next Next z1 = 0 For car = 25 To 49 z1 = z1 + mis(byear, 64, car) + mos(byear, 64, car) Next mnew(byear) = z1 Next Open "c /kirakira/gdata/男子新規裁定者1.txt " For Output As #4 For byear = 1985 To 2100 Write #4, byear, mnew(byear) Next Close #4 End Sub
https://w.atwiki.jp/ce00582/pages/1504.html
Private Sub Command1_Click() Dim byear As Single Dim age As Single Dim car As Single Dim mis(1985 To 2100, 15 To 64, 1 To 49) As Single Dim mos(1985 To 2100, 15 To 64, 1 To 49) As Single Dim m2by(1900 To 2100, 15 To 69) As Single Dim f2by(1900 To 2100, 15 To 69) As Single Dim mdeby(1900 To 2100, 0 To 99) As Single Dim fdeby(1900 To 2100, 0 To 99) As Single Dim alpha(15 To 69) As Single Dim beta(15 To 69) As Single Dim gamma(15 To 69) As Single Dim theta(15 To 65) As Single Dim zan(1985 To 2100, 15 To 64, 1 To 49) As Single Dim zant(1985 To 2100, 15 To 64, 1 To 49) As Single Dim mde(1985 To 2100, 0 To 99) As Single Dim mnew(1985 To 2100) As Single Dim z1 As Single Dim z2 As Single Dim z3 As Single Dim v As Single Open "c /nagoya/gdata/変形生命表.txt " For Input As #1 Do Until EOF(1) Input #1, a1, a2, a3, a4 byear = a1 age = a2 mdeby(byear, age) = a3 fdeby(byear, age) = a4 Loop Close #1 Open "c /nagoya/data/男子脱退力.txt " For Input As #2 Do Until EOF(2) Input #2, a1, a2, a3, a4 age = a1 gamma(age) = a2 alpha(age) = a3 beta(age) = a4 Loop Close #2 Open "c /nagoya/data/再加入率.txt " For Input As #3 Do Until EOF(3) Input #3, a1, a2, a3, a4 age = a1 theta(age) = a2 Loop Close #3 Open "c /nagoya/gdata/変形厚生年金被保険者.txt " For Input As #5 Do Until EOF(5) Input #5, a1, a2, a3, a4 byear = a1 age = a2 m2by(byear, age) = a3 f2by(byear, age) = a4 Loop Close #5 For byear = 1990 To 2034 age = 15 mis(byear, age, 1) = m2by(byear, age) For age = 16 To 64 z1 = (1 - gamma(age - 1)) * m2by(byear, age - 1) z2 = m2by(byear, age) - z1 If z2 0 Then z2 = 0 z3 = (1 - theta(age)) * z2 z4 = theta(age) * z2 mis(byear, age, 1) = z3 z5 = 0 For car = 1 To 49 z5 = z5 + mos(byear, age - 1, car) Next If z5 = 0 Then z5 = 1 v = z4 / z5 If v 1 Then v = 1 For car = 2 To 49 mis(byear, age, car) = (1 - gamma(age - 1)) * mis(byear, age - 1, car - 1) + v * mos(byear, age - 1, car - 1) Next For car = 1 To 49 mos(byear, age, car) = (gamma(age - 1) - alpha(age - 1) - beta(age)) * mis(byear, age - 1, car) + (1 - mdeby(byear, age) - v) * mos(byear, age - 1, car) Next Next z1 = 0 For car = 1 To 24 z1 = z1 + mis(byear, 64, car) + mos(byear, 64, car) Next mnew(byear) = z1 Next Open "c /nagoya/gdata/男子通算新規裁定者1.txt " For Output As #4 For byear = 1990 To 2100 Write #4, byear, mnew(byear) Next Close #4 End Sub
https://w.atwiki.jp/ce00582/pages/1908.html
Private Sub Command1_Click() Dim byear As Single Dim age As Single Dim car As Single Dim mis(1985 To 2100, 15 To 64, 1 To 49) As Single Dim mos(1985 To 2100, 15 To 64, 1 To 49) As Single Dim m2by(1900 To 2100, 15 To 69) As Single Dim f2by(1900 To 2100, 15 To 69) As Single Dim mdeby(1900 To 2100, 0 To 99) As Single Dim fdeby(1900 To 2100, 0 To 99) As Single Dim alpha(15 To 69) As Single Dim beta(15 To 69) As Single Dim gamma(15 To 69) As Single Dim theta(15 To 64) As Single Dim zan(1985 To 2100, 15 To 64, 1 To 49) As Single Dim zant(1985 To 2100, 15 To 64, 1 To 49) As Single Dim mde(1985 To 2100, 0 To 99) As Single Dim fnew(1985 To 2100) As Single Dim z1 As Single Dim z2 As Single Dim z3 As Single Dim v As Single Open "c /dig/data/女子脱退力.txt " For Input As #2 Do Until EOF(2) Input #2, a1, a2, a3, a4 age = a1 gamma(age) = a2 alpha(age) = a3 beta(age) = a4 Loop Close #2 Open "c /dig/data/再加入率.txt " For Input As #3 Do Until EOF(3) Input #3, a1, a2, a3, a4 age = a1 theta(age) = a3 Loop Close #3 Open "c /dig/gdata/変形厚生年金被保険者.txt " For Input As #5 Do Until EOF(5) Input #5, a1, a2, a3, a4 byear = a1 age = a2 m2by(byear, age) = a3 f2by(byear, age) = a4 Loop Close #5 For byear = 1990 To 2034 age = 15 mis(byear, age, 1) = f2by(byear, age) For age = 16 To 64 z1 = (1 - gamma(age - 1)) * f2by(byear, age - 1) z2 = f2by(byear, age) - z1 If z2 0 Then z2 = 0 z3 = (1 - theta(age)) * z2 z4 = theta(age) * z2 mis(byear, age, 1) = z3 z5 = 0 For car = 1 To 49 z5 = z5 + mos(byear, age - 1, car) Next If z5 = 0 Then z5 = 1 v = z4 / z5 If v 1 Then v = 1 For car = 2 To 49 mis(byear, age, car) = (1 - gamma(age - 1)) * mis(byear, age - 1, car - 1) + v * mos(byear, age - 1, car - 1) Next For car = 1 To 49 mos(byear, age, car) = (gamma(age - 1) - alpha(age - 1) - beta(age)) * mis(byear, age - 1, car) + (1 - alpha(age - 1) - v) * mos(byear, age - 1, car) Next Next z1 = 0 z2 = 0 For car = 1 To 24 z1 = z1 + mis(byear, 64, car) + mos(byear, 64, car) z2 = z2 + car * (mis(byear, 64, car) + mos(byear, 64, car)) Next fnew(byear) = z2 / z1 Next Open "c /dig/gdata/女子通算平均加入年数1.txt " For Output As #4 For byear = 1990 To 2100 Write #4, byear, fnew(byear) Next Close #4 End Sub
https://w.atwiki.jp/hmiku/pages/9761.html
【登録タグ 21世紀PCD AMAGICD CD CDP TEMB／ブランコPCD buzzGCD koukiCD ぽわぽわPCD シメサバツイスターズCD ファミマPCD ミュムPCD ユミソラCD ンジャメナPCD 単色PCD 大空PCD 糞田舎PCD 風呂埋葬PCD 鬼畜ショタPCD】 前作 本作 次作 - Petal - ぽわぽわP 大空P シメサバツイスターズ kouki ンジャメナP 単色P TEMB／ブランコP buzzG ファミマP 鬼畜ショタP ユミソラ AMAGI ミュムP 21世紀P 風呂埋葬P 糞田舎P 即売 同人 発売 2010年05月09日 価格 ￥1,000 ￥1,260(税込) サークル bloom ジャケットイラスト・デザイン：Haq マスタリング：Dios/シグナルP デザイン協力：ユミソラ とらのあなで購入する CD紹介 総勢18名のクリエイターが贈る、「花」をテーマにしたコンピレーション・アルバム。 THE VOC@LOID M@STER 12（ボーマス12）にて頒布。 「是非1曲目から通して聴いて欲しい」と、曲順への強い拘りも示している。 現在、とらのあなで委託販売が行われている。 曲目 曲名 作者 テーマ(花) 1 ジニアとミーム ぽわぽわP ジニア 2 Cat tail 大空P ねこやなぎ 3 独裁者ヒマワリ シメサバツイスターズ ひまわり 4 フリージアの記憶 kouki フリージア 5 rainy season もちごめ 梅 6 Liam 単色P ニゲラ 7 春風エンドロール TEMB 桜 8 Marygold buzzG マリーゴールド 9 霞草 Ruco(ファミマP) 霞草 10 ロベリア 作詞ユミソラ作曲sequel(鬼畜ショタP) ロベリア 11 占いとコスモス AMAGI コスモス 12 ERiKA ミュムP エリカ 13 黄色の一輪 21世紀P キンミズヒキ 14 シラミレミ 36g（風呂埋葬P） シラー 15 Pear 糞田舎P 梨 コメント CD初収録のP多いね。個人的には単色PとぽわぽわPがイチオシ。 -- 名無しさん (2010-04-27 08 00 41) buzzさんいるなら買うわ -- 名無しさん (2010-04-29 01 19 14) シラミレミとLiamとジニアとミームが入ってる？buzzさんとくそ田舎P参加？ふむ、よし買おう -- 名無しさん (2011-05-01 20 58 27) 名前 コメント
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Private Sub Command1_Click() Dim byear As Single Dim age As Single Dim car As Single Dim mis(1985 To 2100, 15 To 64, 1 To 49) As Single Dim mos(1985 To 2100, 15 To 64, 1 To 49) As Single Dim m2by(1900 To 2100, 15 To 69) As Single Dim f2by(1900 To 2100, 15 To 69) As Single Dim mdeby(1900 To 2100, 0 To 99) As Single Dim fdeby(1900 To 2100, 0 To 99) As Single Dim alpha(15 To 69) As Single Dim beta(15 To 69) As Single Dim gamma(15 To 69) As Single Dim theta(15 To 65) As Single Dim zan(1985 To 2100, 15 To 64, 1 To 49) As Single Dim zant(1985 To 2100, 15 To 64, 1 To 49) As Single Dim mde(1985 To 2100, 0 To 99) As Single Dim mnew(1985 To 2100) As Single Dim z1 As Single Dim z2 As Single Dim z3 As Single Dim v As Single Open "c /dig/data/男子脱退力.txt " For Input As #2 Do Until EOF(2) Input #2, a1, a2, a3, a4 age = a1 gamma(age) = a2 alpha(age) = a3 beta(age) = a4 Loop Close #2 Open "c /dig/data/再加入率.txt " For Input As #3 Do Until EOF(3) Input #3, a1, a2, a3, a4 age = a1 theta(age) = a2 Loop Close #3 Open "c /dig/gdata/変形厚生年金被保険者.txt " For Input As #5 Do Until EOF(5) Input #5, a1, a2, a3, a4 byear = a1 age = a2 m2by(byear, age) = a3 f2by(byear, age) = a4 Loop Close #5 For byear = 1990 To 2034 age = 15 mis(byear, age, 1) = m2by(byear, age) For age = 16 To 64 z1 = (1 - gamma(age - 1)) * m2by(byear, age - 1) z2 = m2by(byear, age) - z1 If z2 0 Then z2 = 0 z3 = (1 - theta(age)) * z2 z4 = theta(age) * z2 mis(byear, age, 1) = z3 z5 = 0 For car = 1 To 49 z5 = z5 + mos(byear, age - 1, car) Next If z5 = 0 Then z5 = 1 v = z4 / z5 If v 1 Then v = 1 For car = 2 To 49 mis(byear, age, car) = (1 - gamma(age - 1)) * mis(byear, age - 1, car - 1) + v * mos(byear, age - 1, car - 1) Next For car = 1 To 49 mos(byear, age, car) = (gamma(age - 1) - alpha(age - 1) - beta(age)) * mis(byear, age - 1, car) + (1 - alpha(age - 1) - v) * mos(byear, age - 1, car) Next Next z1 = 0 z2 = 0 For car = 25 To 49 z1 = z1 + mis(byear, 64, car) + mos(byear, 64, car) z2 = z2 + car * (mis(byear, 64, car) + mos(byear, 64, car)) Next mnew(byear) = z2 / z1 Next Open "c /dig/gdata/男子平均加入年数1.txt " For Output As #4 For byear = 1990 To 2100 Write #4, byear, mnew(byear) Next Close #4 End Sub